(ellipses) APPLYING MULTISTART
(ellipses) SEED = 1
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 3.2D-02
 Smallest constraints scale factor : 8.9D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -1.573D+02 4.D+00 -5.026D+00 4.D+00 4.D+00 9.D-01 2.D+00    0   0   0
  1 4.D+00 -3.469D+02 1.D+00 -1.108D+01 1.D+00 1.D+00 6.D-01 4.D-01   10C  0   0
  2 9.D+01 -2.026D+02 1.D+00 -6.471D+00 1.D+00 1.D+00 2.D-05 6.D-03   33C  0   0
  3 9.D+02 -2.000D+02 1.D+00 -6.389D+00 1.D+00 1.D+00 5.D-09 4.D-06   41C  0   0
  4 9.D+03 -2.000D+02 1.D+00 -6.389D+00 1.D+00 1.D+00 2.D-08 2.D-10   43C  0   0
  5 9.D+04 -2.000D+02 1.D+00 -6.389D+00 1.D+00 1.D+00 2.D-05 2.D-10   43C  0   0
  6 9.D+05 -2.000D+02 1.D+00 -6.389D+00 1.D+00 1.D+00 1.D-05 3.D-11   44C  0   0
  7 9.D+06 -2.000D+02 1.D+00 -6.389D+00 1.D+00 1.D+00 3.D-05 3.D-12   45C  0   0
  8 9.D+07 -2.000D+02 1.D+00 -6.389D+00 1.D+00 1.D+00 5.D-07 3.D-13   47C  0   0
  9 9.D+08 -2.000D+02 1.D+00 -6.389D+00 1.D+00 1.D+00 6.D-06 6.D-15   48C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 9.D+09 -2.000D+02 1.D+00 -6.389D+00 1.D+00 1.D+00 6.D-05 6.D-15   48C  0   0
 11 9.D+10 -2.000D+02 1.D+00 -6.389D+00 1.D+00 1.D+00 1.D+02 1.D-09   80P  0   0
 12 9.D+11 -2.000D+02 1.D+00 -6.389D+00 1.D+00 1.D+00 9.D+01 1.D-10  129P  0   0
 13 9.D+12 -2.000D+02 1.D+00 -6.389D+00 1.D+00 1.D+00 2.D+02 2.D-11  158P  0   0
 14 9.D+13 -2.000D+02 1.D+00 -6.389D+00 1.D+00 1.D+00 6.D+03 6.D-11  380P  0   0
 15 9.D+14 -2.000D+02 1.D+00 -6.389D+00 1.D+00 1.D+00 4.D+00 6.D-12  408P  0   0
 16 9.D+15 -2.000D+02 1.D+00 -6.389D+00 1.D+00 1.D+00 2.D+06 2.D-10  875P  0   0
 17 9.D+16 -2.000D+02 1.D+00 -6.389D+00 1.D+00 1.D+00 1.D+02 2.D-11 1875M  0   0
 18 9.D+17 -2.000D+02 1.D+00 -6.389D+00 1.D+00 1.D+00 2.D+03 2.D-15 2875M  0   0
 19 9.D+18 -2.000D+02 1.D+00 -6.389D+00 1.D+00 1.D+00 7.D+04 8.D-15 2879P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 9.D+19 -2.000D+02 1.D+00 -6.389D+00 1.D+00 1.D+00 2.D+08 2.D-12 2883P  0   0
 21 9.D+20 -2.000D+02 1.D+00 -6.389D+00 1.D+00 1.D+00 4.D+06 2.D-13 2894P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.63

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):  13207
 Subroutine evalg    (coded=T):   4883
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T): 302934 ( 15146 calls per constraint in average)
 Subroutine evaljac  (coded=T):  52196 (  2609 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):   2893
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 2
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 2.4D-02
 Smallest constraints scale factor : 5.5D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -1.175D+02 2.D+00 -2.787D+00 1.D+00 1.D+00 7.D-01 1.D+00    0   0   0
  1 1.D+01 -2.509D+02 1.D+00 -5.949D+00 4.D-01 4.D-01 1.D+00 2.D-01   10C  0   0
  2 6.D+01 -1.882D+02 1.D+00 -4.464D+00 3.D-01 3.D-01 1.D-05 1.D-02   34C  0   0
  3 6.D+02 -1.883D+02 1.D+00 -4.465D+00 3.D-01 3.D-01 4.D-05 5.D-04   45C  0   0
  4 6.D+03 -1.883D+02 1.D+00 -4.465D+00 3.D-01 3.D-01 3.D-09 1.D-07   49C  0   0
  5 6.D+04 -1.883D+02 1.D+00 -4.465D+00 3.D-01 3.D-01 1.D-08 7.D-12   51C  0   0
  6 6.D+05 -1.883D+02 1.D+00 -4.465D+00 3.D-01 3.D-01 3.D-06 7.D-12   51C  0   0
  7 6.D+06 -1.883D+02 1.D+00 -4.465D+00 3.D-01 3.D-01 4.D-05 7.D-12   51C  0   0
  8 6.D+07 -1.883D+02 1.D+00 -4.465D+00 3.D-01 3.D-01 1.D-05 7.D-13   52C  0   0
  9 6.D+08 -1.883D+02 1.D+00 -4.465D+00 3.D-01 3.D-01 3.D-05 4.D-14   53C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 6.D+09 -1.883D+02 1.D+00 -4.465D+00 3.D-01 3.D-01 3.D-05 1.D-14   54C  0   0
 11 6.D+10 -1.883D+02 1.D+00 -4.465D+00 3.D-01 3.D-01 3.D-05 4.D-16   55C  0   0
 12 6.D+11 -1.883D+02 1.D+00 -4.465D+00 3.D-01 3.D-01 5.D-04 3.D-16   59P  0   0
 13 6.D+12 -1.883D+02 1.D+00 -4.465D+00 3.D-01 3.D-01 6.D-03 1.D-15   64P  0   0
 14 6.D+13 -1.883D+02 1.D+00 -4.465D+00 3.D-01 3.D-01 8.D-02 3.D-16   68P  0   0
 15 6.D+14 -1.883D+02 1.D+00 -4.465D+00 3.D-01 3.D-01 2.D+06 9.D-09   72P  0   0
 16 6.D+15 -1.883D+02 1.D+00 -4.465D+00 3.D-01 3.D-01 1.D+07 5.D-09  108P  0   0
 17 6.D+16 -1.883D+02 1.D+00 -4.465D+00 3.D-01 3.D-01 4.D+07 1.D-09  206P  0   0
 18 6.D+17 -1.883D+02 1.D+00 -4.465D+00 3.D-01 3.D-01 6.D+04 7.D-13  298P  0   0
 19 6.D+18 -1.883D+02 1.D+00 -4.465D+00 3.D-01 3.D-01 7.D+09 3.D-09  303P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 6.D+19 -1.883D+02 1.D+00 -4.465D+00 3.D-01 3.D-01 7.D+10 3.D-09  372P  0   0
 21 6.D+20 -1.883D+02 1.D+00 -4.465D+00 3.D-01 3.D-01 7.D+11 3.D-09  446P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.13

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   2133
 Subroutine evalg    (coded=T):    532
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  43303 (  2165 calls per constraint in average)
 Subroutine evaljac  (coded=T):   5925 (   296 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    446
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 3
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 2.9D-02
 Smallest constraints scale factor : 8.5D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -1.245D+02 2.D+00 -3.573D+00 1.D+00 1.D+00 1.D+00 6.D-01    0   0   0
  1 2.D+01 -1.720D+02 1.D+00 -4.937D+00 1.D+00 1.D+00 2.D-01 8.D-02   10C  0   0
  2 5.D+01 -1.645D+02 1.D+00 -4.721D+00 1.D+00 1.D+00 3.D-05 8.D-03   37C  0   0
  3 5.D+02 -1.627D+02 1.D+00 -4.669D+00 1.D+00 1.D+00 5.D-05 2.D-05   56C  0   0
  4 5.D+03 -1.627D+02 1.D+00 -4.669D+00 1.D+00 1.D+00 7.D-06 2.D-08   60C  0   0
  5 5.D+04 -1.627D+02 1.D+00 -4.669D+00 1.D+00 1.D+00 1.D-05 3.D-10   61C  0   0
  6 5.D+05 -1.627D+02 1.D+00 -4.669D+00 1.D+00 1.D+00 1.D-05 3.D-11   62C  0   0
  7 5.D+06 -1.627D+02 1.D+00 -4.669D+00 1.D+00 1.D+00 3.D-06 1.D-12   63C  0   0
  8 5.D+07 -1.627D+02 1.D+00 -4.669D+00 1.D+00 1.D+00 5.D-06 1.D-13   64C  0   0
  9 5.D+08 -1.627D+02 1.D+00 -4.669D+00 1.D+00 1.D+00 5.D-05 1.D-13   64C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 5.D+09 -1.627D+02 1.D+00 -4.669D+00 1.D+00 1.D+00 8.D-06 9.D-15   65C  0   0
 11 5.D+10 -1.627D+02 1.D+00 -4.669D+00 1.D+00 1.D+00 4.D-05 6.D-16   66C  0   0
 12 5.D+11 -1.627D+02 1.D+00 -4.669D+00 1.D+00 1.D+00 2.D+02 2.D-09   72P  0   0
 13 5.D+12 -1.627D+02 1.D+00 -4.669D+00 1.D+00 1.D+00 2.D+03 3.D-10  176P  0   0
 14 5.D+13 -1.627D+02 1.D+00 -4.669D+00 1.D+00 1.D+00 5.D+03 4.D-10  184P  0   0
 15 5.D+14 -1.627D+02 1.D+00 -4.669D+00 1.D+00 1.D+00 5.D+05 1.D-09  338P  0   0
 16 5.D+15 -1.627D+02 1.D+00 -4.669D+00 1.D+00 1.D+00 7.D+06 6.D-09  351P  0   0
 17 5.D+16 -1.627D+02 1.D+00 -4.669D+00 1.D+00 1.D+00 2.D+08 2.D-08  373P  0   0
 18 5.D+17 -1.627D+02 1.D+00 -4.669D+00 1.D+00 1.D+00 9.D+08 7.D-09  384P  0   0
 19 5.D+18 -1.627D+02 1.D+00 -4.669D+00 1.D+00 1.D+00 2.D+10 1.D-08  436P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 5.D+19 -1.627D+02 1.D+00 -4.669D+00 1.D+00 1.D+00 4.D+08 8.D-12  457P  0   0
 21 5.D+20 -1.627D+02 1.D+00 -4.669D+00 1.D+00 1.D+00 1.D+11 8.D-10  461P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.14

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   2277
 Subroutine evalg    (coded=T):    540
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  46068 (  2303 calls per constraint in average)
 Subroutine evaljac  (coded=T):   6372 (   318 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    459
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 4
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 2.8D-02
 Smallest constraints scale factor : 8.3D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -1.277D+02 2.D+00 -3.620D+00 1.D+00 1.D+00 1.D+00 9.D-01    0   0   0
  1 1.D+01 -1.848D+02 1.D+00 -5.238D+00 1.D+00 1.D+00 1.D+00 1.D-01   10C  0   0
  2 5.D+01 -1.913D+02 1.D+00 -5.422D+00 1.D+00 1.D+00 4.D-08 1.D-02   73C  0   0
  3 5.D+02 -1.868D+02 1.D+00 -5.297D+00 1.D+00 1.D+00 7.D-05 3.D-05   77C  0   0
  4 5.D+03 -1.869D+02 1.D+00 -5.297D+00 1.D+00 1.D+00 5.D-05 2.D-08   79C  0   0
  5 5.D+04 -1.869D+02 1.D+00 -5.297D+00 1.D+00 1.D+00 4.D-05 1.D-09   80C  0   0
  6 5.D+05 -1.869D+02 1.D+00 -5.297D+00 1.D+00 1.D+00 2.D-05 6.D-11   83C  0   0
  7 5.D+06 -1.869D+02 1.D+00 -5.297D+00 1.D+00 1.D+00 3.D-05 9.D-12   84C  0   0
  8 5.D+07 -1.869D+02 1.D+00 -5.297D+00 1.D+00 1.D+00 2.D-05 7.D-13   85C  0   0
  9 5.D+08 -1.869D+02 1.D+00 -5.297D+00 1.D+00 1.D+00 2.D-05 5.D-14   86C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 5.D+09 -1.869D+02 1.D+00 -5.297D+00 1.D+00 1.D+00 2.D-05 4.D-15   87C  0   0
 11 5.D+10 -1.869D+02 1.D+00 -5.297D+00 1.D+00 1.D+00 7.D-05 1.D-15   88C  0   0
 12 5.D+11 -1.869D+02 1.D+00 -5.297D+00 1.D+00 1.D+00 7.D-04 1.D-15   95P  0   0
 13 5.D+12 -1.869D+02 1.D+00 -5.297D+00 1.D+00 1.D+00 4.D-03 8.D-16  102P  0   0
 14 5.D+13 -1.869D+02 1.D+00 -5.297D+00 1.D+00 1.D+00 2.D-02 4.D-16  106P  0   0
 15 5.D+14 -1.869D+02 1.D+00 -5.297D+00 1.D+00 1.D+00 4.D-01 6.D-17  109P  0   0
 16 5.D+15 -1.869D+02 1.D+00 -5.297D+00 1.D+00 1.D+00 5.D+07 3.D-08  113P  0   0
 17 5.D+16 -1.869D+02 1.D+00 -5.297D+00 1.D+00 1.D+00 1.D+06 9.D-11  117P  0   0
 18 5.D+17 -1.869D+02 1.D+00 -5.297D+00 1.D+00 1.D+00 2.D+09 4.D-09  125P  0   0
 19 5.D+18 -1.869D+02 1.D+00 -5.297D+00 1.D+00 1.D+00 3.D+10 2.D-08  284P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 5.D+19 -1.869D+02 1.D+00 -5.297D+00 1.D+00 1.D+00 3.D+11 2.D-08  332P  0   0
 21 5.D+20 -1.869D+02 1.D+00 -5.297D+00 1.D+00 1.D+00 3.D+12 2.D-08  399P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.12

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   2024
 Subroutine evalg    (coded=T):    499
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  41412 (  2070 calls per constraint in average)
 Subroutine evaljac  (coded=T):   5445 (   272 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    397
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 5
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 3.0D-02
 Smallest constraints scale factor : 9.8D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -9.433D+01 4.D+00 -2.811D+00 3.D+00 3.D+00 1.D+00 4.D+00    0   0   0
  1 2.D+00 -3.848D+02 2.D+00 -1.147D+01 1.D+00 1.D+00 1.D+00 6.D-01   10C  0   0
  2 5.D+01 -1.783D+02 1.D+00 -5.315D+00 1.D+00 1.D+00 2.D-05 2.D-02   38C  0   0
  3 5.D+02 -1.733D+02 1.D+00 -5.164D+00 1.D+00 1.D+00 3.D-07 9.D-05   52C  0   0
  4 5.D+03 -1.807D+02 1.D+00 -5.385D+00 1.D+00 1.D+00 2.D-05 2.D-04  156C  0   0
  5 5.D+04 -1.807D+02 1.D+00 -5.385D+00 1.D+00 1.D+00 1.D-06 3.D-09  162C  0   0
  6 5.D+05 -1.807D+02 1.D+00 -5.385D+00 1.D+00 1.D+00 4.D-10 2.D-12  167C  0   0
  7 5.D+06 -1.807D+02 1.D+00 -5.385D+00 1.D+00 1.D+00 1.D-05 2.D-12  167C  0   0
  8 5.D+07 -1.807D+02 1.D+00 -5.385D+00 1.D+00 1.D+00 6.D-06 1.D-13  168C  0   0
  9 5.D+08 -1.807D+02 1.D+00 -5.385D+00 1.D+00 1.D+00 4.D-06 2.D-14  169C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 5.D+09 -1.807D+02 1.D+00 -5.385D+00 1.D+00 1.D+00 6.D-05 2.D-14  169C  0   0
 11 5.D+10 -1.807D+02 1.D+00 -5.385D+00 1.D+00 1.D+00 2.D-05 1.D-15  170C  0   0
 12 5.D+11 -1.807D+02 1.D+00 -5.385D+00 1.D+00 1.D+00 3.D-04 6.D-16  176P  0   0
 13 5.D+12 -1.807D+02 1.D+00 -5.385D+00 1.D+00 1.D+00 4.D-03 7.D-16  181P  0   0
 14 5.D+13 -1.807D+02 1.D+00 -5.385D+00 1.D+00 1.D+00 3.D-02 6.D-16  184P  0   0
 15 5.D+14 -1.807D+02 1.D+00 -5.385D+00 1.D+00 1.D+00 2.D-01 3.D-16  189P  0   0
 16 5.D+15 -1.807D+02 1.D+00 -5.385D+00 1.D+00 1.D+00 2.D+07 1.D-08  195P  0   0
 17 5.D+16 -1.807D+02 1.D+00 -5.385D+00 1.D+00 1.D+00 4.D+08 3.D-08  222P  0   0
 18 5.D+17 -1.807D+02 1.D+00 -5.385D+00 1.D+00 1.D+00 2.D+08 2.D-09  227P  0   0
 19 5.D+18 -1.807D+02 1.D+00 -5.385D+00 1.D+00 1.D+00 9.D+10 6.D-08  231P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 5.D+19 -1.807D+02 1.D+00 -5.385D+00 1.D+00 1.D+00 2.D+11 9.D-09  236P  0   0
 21 5.D+20 -1.807D+02 1.D+00 -5.385D+00 1.D+00 1.D+00 2.D+12 1.D-08  287P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.05

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   1009
 Subroutine evalg    (coded=T):    410
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  21538 (  1076 calls per constraint in average)
 Subroutine evaljac  (coded=T):   4769 (   238 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    283
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 6
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 4.4D-02
 Smallest constraints scale factor : 1.0D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -7.911D+01 4.D+00 -3.519D+00 2.D+00 2.D+00 1.D+00 8.D-01    0   0   0
  1 1.D+01 -3.370D+02 1.D+00 -1.499D+01 1.D+00 1.D+00 5.D-01 2.D-01   10C  0   0
  2 1.D+02 -2.013D+02 1.D+00 -8.955D+00 1.D+00 1.D+00 4.D-05 4.D-03   26C  0   0
  3 1.D+03 -2.014D+02 1.D+00 -8.959D+00 1.D+00 1.D+00 4.D-05 2.D-05   30C  0   0
  4 1.D+04 -2.014D+02 1.D+00 -8.959D+00 1.D+00 1.D+00 1.D-07 2.D-09   32C  0   0
  5 1.D+05 -2.014D+02 1.D+00 -8.959D+00 1.D+00 1.D+00 2.D-05 3.D-10   33C  0   0
  6 1.D+06 -2.014D+02 1.D+00 -8.959D+00 1.D+00 1.D+00 2.D-05 1.D-11   34C  0   0
  7 1.D+07 -2.014D+02 1.D+00 -8.959D+00 1.D+00 1.D+00 3.D-05 2.D-12   35C  0   0
  8 1.D+08 -2.014D+02 1.D+00 -8.959D+00 1.D+00 1.D+00 1.D-05 2.D-13   36C  0   0
  9 1.D+09 -2.014D+02 1.D+00 -8.959D+00 1.D+00 1.D+00 3.D-05 1.D-14   37C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 1.D+10 -2.014D+02 1.D+00 -8.959D+00 1.D+00 1.D+00 2.D-05 1.D-15   38C  0   0
 11 1.D+11 -2.014D+02 1.D+00 -8.959D+00 1.D+00 1.D+00 4.D-05 1.D-16   42C  0   0
 12 1.D+12 -2.014D+02 1.D+00 -8.959D+00 1.D+00 1.D+00 4.D-04 7.D-17   46P  0   0
 13 1.D+13 -2.014D+02 1.D+00 -8.959D+00 1.D+00 1.D+00 3.D-03 2.D-16   53P  0   0
 14 1.D+14 -2.014D+02 1.D+00 -8.959D+00 1.D+00 1.D+00 3.D-03 0.D+00   59P  0   0
 15 1.D+15 -2.014D+02 1.D+00 -8.959D+00 1.D+00 1.D+00 1.D-01 1.D-16   62P  0   0
 16 1.D+16 -2.014D+02 1.D+00 -8.959D+00 1.D+00 1.D+00 2.D+00 1.D-16   65P  0   0
 17 1.D+17 -2.014D+02 1.D+00 -8.959D+00 1.D+00 1.D+00 1.D+09 8.D-09   69P  0   0
 18 1.D+18 -2.014D+02 1.D+00 -8.959D+00 1.D+00 1.D+00 1.D+09 2.D-09   74P  0   0
 19 1.D+19 -2.014D+02 1.D+00 -8.959D+00 1.D+00 1.D+00 8.D+10 6.D-09   79P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 1.D+20 -2.014D+02 1.D+00 -8.959D+00 1.D+00 1.D+00 6.D+10 1.D-09   84P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.03

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):    296
 Subroutine evalg    (coded=T):    154
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):   6316 (   315 calls per constraint in average)
 Subroutine evaljac  (coded=T):   1797 (    89 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):     84
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 7
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 2.9D-02
 Smallest constraints scale factor : 8.9D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -8.973D+01 2.D+00 -2.613D+00 1.D+00 1.D+00 7.D-01 8.D-01    0   0   0
  1 1.D+01 -2.103D+02 1.D+00 -6.123D+00 5.D-01 5.D-01 1.D+00 2.D-01   10C  0   0
  2 6.D+01 -1.910D+02 1.D+00 -5.562D+00 5.D-01 5.D-01 6.D-05 3.D-02   55C  0   0
  3 6.D+02 -1.869D+02 1.D+00 -5.442D+00 5.D-01 5.D-01 6.D-05 3.D-05   61C  0   0
  4 6.D+03 -1.869D+02 1.D+00 -5.442D+00 5.D-01 5.D-01 9.D-06 9.D-09   63C  0   0
  5 6.D+04 -1.869D+02 1.D+00 -5.442D+00 5.D-01 5.D-01 6.D-06 2.D-10   64C  0   0
  6 6.D+05 -1.869D+02 1.D+00 -5.442D+00 5.D-01 5.D-01 1.D-04 2.D-10   64C  0   0
  7 6.D+06 -1.869D+02 1.D+00 -5.442D+00 5.D-01 5.D-01 8.D-08 1.D-11   68C  0   0
  8 6.D+07 -1.869D+02 1.D+00 -5.442D+00 5.D-01 5.D-01 3.D-05 5.D-13   69C  0   0
  9 6.D+08 -1.869D+02 1.D+00 -5.442D+00 5.D-01 5.D-01 1.D-05 3.D-14   70C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 6.D+09 -1.869D+02 1.D+00 -5.442D+00 5.D-01 5.D-01 5.D-05 5.D-15   71C  0   0
 11 6.D+10 -1.869D+02 1.D+00 -5.442D+00 5.D-01 5.D-01 5.D-05 8.D-16   74C  0   0
 12 6.D+11 -1.869D+02 1.D+00 -5.442D+00 5.D-01 5.D-01 2.D-04 4.D-16   82P  0   0
 13 6.D+12 -1.869D+02 1.D+00 -5.442D+00 5.D-01 5.D-01 7.D-03 1.D-15   85P  0   0
 14 6.D+13 -1.869D+02 1.D+00 -5.442D+00 5.D-01 5.D-01 4.D-02 7.D-16   91P  0   0
 15 6.D+14 -1.869D+02 1.D+00 -5.442D+00 5.D-01 5.D-01 2.D+06 1.D-08   95P  0   0
 16 6.D+15 -1.869D+02 1.D+00 -5.442D+00 5.D-01 5.D-01 2.D+07 1.D-08   99P  0   0
 17 6.D+16 -1.869D+02 1.D+00 -5.442D+00 5.D-01 5.D-01 8.D+05 5.D-11  119P  0   0
 18 6.D+17 -1.869D+02 1.D+00 -5.442D+00 5.D-01 5.D-01 2.D+07 2.D-10  123P  0   0
 19 6.D+18 -1.869D+02 1.D+00 -5.442D+00 5.D-01 5.D-01 8.D+09 5.D-09  127P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 6.D+19 -1.869D+02 1.D+00 -5.442D+00 5.D-01 5.D-01 1.D+09 1.D-12  158P  0   0
 21 6.D+20 -1.869D+02 1.D+00 -5.442D+00 5.D-01 5.D-01 6.D+11 4.D-09  162P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.04

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):    706
 Subroutine evalg    (coded=T):    250
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  14822 (   741 calls per constraint in average)
 Subroutine evaljac  (coded=T):   2833 (   141 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    161
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 8
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 2.0D-02
 Smallest constraints scale factor : 5.7D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -1.824D+02 3.D+00 -3.644D+00 1.D+00 1.D+00 6.D-01 8.D-01    0   0   0
  1 2.D+01 -2.408D+02 1.D+00 -4.810D+00 1.D+00 1.D+00 8.D-01 4.D-02   10C  0   0
  2 5.D+01 -2.543D+02 1.D+00 -5.079D+00 1.D+00 1.D+00 2.D-06 1.D-02   42C  0   0
  3 5.D+02 -2.494D+02 1.D+00 -4.981D+00 1.D+00 1.D+00 2.D-07 4.D-05   49C  0   0
  4 5.D+03 -2.494D+02 1.D+00 -4.981D+00 1.D+00 1.D+00 4.D-08 3.D-08   52C  0   0
  5 5.D+04 -2.494D+02 1.D+00 -4.981D+00 1.D+00 1.D+00 8.D-10 2.D-12   54C  0   0
  6 5.D+05 -2.494D+02 1.D+00 -4.981D+00 1.D+00 1.D+00 1.D-06 2.D-12   54C  0   0
  7 5.D+06 -2.494D+02 1.D+00 -4.981D+00 1.D+00 1.D+00 1.D-05 2.D-12   54C  0   0
  8 5.D+07 -2.494D+02 1.D+00 -4.981D+00 1.D+00 1.D+00 8.D-06 3.D-13   55C  0   0
  9 5.D+08 -2.494D+02 1.D+00 -4.981D+00 1.D+00 1.D+00 1.D-05 2.D-14   56C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 5.D+09 -2.494D+02 1.D+00 -4.981D+00 1.D+00 1.D+00 8.D-06 2.D-15   57C  0   0
 11 5.D+10 -2.494D+02 1.D+00 -4.981D+00 1.D+00 1.D+00 3.D-05 5.D-16   58C  0   0
 12 5.D+11 -2.494D+02 1.D+00 -4.981D+00 1.D+00 1.D+00 1.D+02 8.D-10   66P  0   0
 13 5.D+12 -2.494D+02 1.D+00 -4.981D+00 1.D+00 1.D+00 2.D+03 4.D-10  228P  0   0
 14 5.D+13 -2.494D+02 1.D+00 -4.981D+00 1.D+00 1.D+00 5.D+04 2.D-09  232P  0   0
 15 5.D+14 -2.494D+02 1.D+00 -4.981D+00 1.D+00 1.D+00 2.D+05 1.D-09  263P  0   0
 16 5.D+15 -2.494D+02 1.D+00 -4.981D+00 1.D+00 1.D+00 3.D+06 1.D-09  269P  0   0
 17 5.D+16 -2.494D+02 1.D+00 -4.981D+00 1.D+00 1.D+00 1.D+08 7.D-09  484P  0   0
 18 5.D+17 -2.494D+02 1.D+00 -4.981D+00 1.D+00 1.D+00 4.D+08 8.D-10  555P  0   0
 19 5.D+18 -2.494D+02 1.D+00 -4.981D+00 1.D+00 1.D+00 7.D+09 2.D-09  613P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 5.D+19 -2.494D+02 1.D+00 -4.981D+00 1.D+00 1.D+00 5.D+07 5.D-13  620P  0   0
 21 5.D+20 -2.494D+02 1.D+00 -4.981D+00 1.D+00 1.D+00 6.D+11 1.D-09  626P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.18

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   3089
 Subroutine evalg    (coded=T):    706
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  62347 (  3117 calls per constraint in average)
 Subroutine evaljac  (coded=T):   7662 (   383 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    624
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 9
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 4.8D-02
 Smallest constraints scale factor : 1.3D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -4.731D+01 4.D+00 -2.267D+00 4.D+00 4.D+00 1.D+00 4.D+00    0   0   0
  1 1.D+00 -1.095D+03 4.D+00 -5.247D+01 3.D+00 3.D+00 1.D+00 3.D+00   10C  0   0
  2 3.D+01 -2.658D+02 1.D+00 -1.274D+01 1.D+00 1.D+00 2.D-05 4.D-02   37C  0   0
  3 3.D+01 -2.560D+02 1.D+00 -1.227D+01 1.D+00 1.D+00 3.D-08 3.D-03   41C  0   0
  4 3.D+02 -2.559D+02 1.D+00 -1.226D+01 1.D+00 1.D+00 1.D-06 5.D-05   44C  0   0
  5 3.D+03 -2.559D+02 1.D+00 -1.226D+01 1.D+00 1.D+00 2.D-05 5.D-08   46C  0   0
  6 3.D+04 -2.559D+02 1.D+00 -1.226D+01 1.D+00 1.D+00 3.D-10 7.D-10   48C  0   0
  7 3.D+05 -2.559D+02 1.D+00 -1.226D+01 1.D+00 1.D+00 9.D-05 3.D-10   50C  0   0
  8 3.D+06 -2.559D+02 1.D+00 -1.226D+01 1.D+00 1.D+00 4.D-05 2.D-11   51C  0   0
  9 3.D+07 -2.559D+02 1.D+00 -1.226D+01 1.D+00 1.D+00 7.D-05 2.D-12   52C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 3.D+08 -2.559D+02 1.D+00 -1.226D+01 1.D+00 1.D+00 3.D-05 2.D-13   53C  0   0
 11 3.D+09 -2.559D+02 1.D+00 -1.226D+01 1.D+00 1.D+00 5.D-05 2.D-14   54C  0   0
 12 3.D+10 -2.559D+02 1.D+00 -1.226D+01 1.D+00 1.D+00 1.D-05 2.D-15   55C  0   0
 13 3.D+11 -2.559D+02 1.D+00 -1.226D+01 1.D+00 1.D+00 4.D-05 1.D-16   56C  0   0
 14 3.D+12 -2.559D+02 1.D+00 -1.226D+01 1.D+00 1.D+00 3.D+04 1.D-08  164P  0   0
 15 3.D+13 -2.559D+02 1.D+00 -1.226D+01 1.D+00 1.D+00 3.D+04 1.D-09  171P  0   0
 16 3.D+14 -2.559D+02 1.D+00 -1.226D+01 1.D+00 1.D+00 1.D+05 3.D-10  200P  0   0
 17 3.D+15 -2.559D+02 1.D+00 -1.226D+01 1.D+00 1.D+00 6.D+06 2.D-09  207P  0   0
 18 3.D+16 -2.559D+02 1.D+00 -1.226D+01 1.D+00 1.D+00 7.D+07 2.D-09  212P  0   0
 19 3.D+17 -2.559D+02 1.D+00 -1.226D+01 1.D+00 1.D+00 5.D+08 1.D-09  240P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 3.D+18 -2.559D+02 1.D+00 -1.226D+01 1.D+00 1.D+00 6.D+09 2.D-09  250P  0   0
 21 3.D+19 -2.559D+02 1.D+00 -1.226D+01 1.D+00 1.D+00 6.D+08 2.D-11  689P  0   0
 22 3.D+20 -2.559D+02 1.D+00 -1.226D+01 1.D+00 1.D+00 5.D+11 1.D-09  695P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.17

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   3383
 Subroutine evalg    (coded=T):    779
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  68253 (  3412 calls per constraint in average)
 Subroutine evaljac  (coded=T):   8737 (   436 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    693
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 10
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 2.8D-02
 Smallest constraints scale factor : 6.2D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -1.314D+02 4.D+00 -3.649D+00 3.D+00 3.D+00 8.D-01 2.D+00    0   0   0
  1 6.D+00 -1.970D+02 1.D+00 -5.470D+00 5.D-01 5.D-01 1.D+00 1.D-01   10C  0   0
  2 5.D+01 -1.649D+02 1.D+00 -4.580D+00 4.D-01 4.D-01 8.D-05 2.D-02   63C  0   0
  3 5.D+02 -1.607D+02 1.D+00 -4.464D+00 4.D-01 4.D-01 8.D-07 1.D-04   79C  0   0
  4 5.D+03 -1.608D+02 1.D+00 -4.464D+00 4.D-01 4.D-01 1.D-06 7.D-08   85C  0   0
  5 5.D+04 -1.608D+02 1.D+00 -4.464D+00 4.D-01 4.D-01 2.D-10 3.D-11   87C  0   0
  6 5.D+05 -1.608D+02 1.D+00 -4.464D+00 4.D-01 4.D-01 1.D-05 3.D-11   87C  0   0
  7 5.D+06 -1.608D+02 1.D+00 -4.464D+00 4.D-01 4.D-01 8.D-06 2.D-12   88C  0   0
  8 5.D+07 -1.608D+02 1.D+00 -4.464D+00 4.D-01 4.D-01 1.D-05 2.D-13   89C  0   0
  9 5.D+08 -1.608D+02 1.D+00 -4.464D+00 4.D-01 4.D-01 5.D-07 1.D-14   90C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 5.D+09 -1.608D+02 1.D+00 -4.464D+00 4.D-01 4.D-01 8.D-06 2.D-15   91C  0   0
 11 5.D+10 -1.608D+02 1.D+00 -4.464D+00 4.D-01 4.D-01 9.D-05 2.D-15   91C  0   0
 12 5.D+11 -1.608D+02 1.D+00 -4.464D+00 4.D-01 4.D-01 1.D-03 2.D-15   96P  0   0
 13 5.D+12 -1.608D+02 1.D+00 -4.464D+00 4.D-01 4.D-01 6.D-03 9.D-16  101P  0   0
 14 5.D+13 -1.608D+02 1.D+00 -4.464D+00 4.D-01 4.D-01 5.D-02 9.D-16  105P  0   0
 15 5.D+14 -1.608D+02 1.D+00 -4.464D+00 4.D-01 4.D-01 5.D-01 2.D-16  110P  0   0
 16 5.D+15 -1.608D+02 1.D+00 -4.464D+00 4.D-01 4.D-01 1.D+07 4.D-09  114P  0   0
 17 5.D+16 -1.608D+02 1.D+00 -4.464D+00 4.D-01 4.D-01 5.D+07 3.D-09  169P  0   0
 18 5.D+17 -1.608D+02 1.D+00 -4.464D+00 4.D-01 4.D-01 3.D+08 2.D-09  182P  0   0
 19 5.D+18 -1.608D+02 1.D+00 -4.464D+00 4.D-01 4.D-01 9.D+09 6.D-09  186P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 5.D+19 -1.608D+02 1.D+00 -4.464D+00 4.D-01 4.D-01 2.D+09 5.D-13  193P  0   0
 21 5.D+20 -1.608D+02 1.D+00 -4.464D+00 4.D-01 4.D-01 2.D+10 6.D-11  197P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.06

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):    823
 Subroutine evalg    (coded=T):    290
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  17248 (   862 calls per constraint in average)
 Subroutine evaljac  (coded=T):   3074 (   153 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    195
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 11
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 4.4D-02
 Smallest constraints scale factor : 1.2D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -8.895D+01 3.D+00 -3.927D+00 1.D+00 1.D+00 9.D-01 2.D+00    0   0   0
  1 9.D+00 -4.086D+02 2.D+00 -1.804D+01 1.D+00 1.D+00 1.D+00 3.D-01   10C  0   0
  2 9.D+01 -2.396D+02 1.D+00 -1.058D+01 1.D+00 1.D+00 1.D-05 2.D-02   42C  0   0
  3 9.D+02 -2.439D+02 1.D+00 -1.077D+01 1.D+00 1.D+00 9.D-08 1.D-03  124C  0   0
  4 9.D+03 -2.438D+02 1.D+00 -1.077D+01 1.D+00 1.D+00 6.D-06 3.D-07  139C  0   0
  5 9.D+04 -2.438D+02 1.D+00 -1.077D+01 1.D+00 1.D+00 5.D-08 6.D-11  141C  0   0
  6 9.D+05 -2.438D+02 1.D+00 -1.077D+01 1.D+00 1.D+00 6.D-05 6.D-11  141C  0   0
  7 9.D+06 -2.438D+02 1.D+00 -1.077D+01 1.D+00 1.D+00 7.D-06 1.D-12  142C  0   0
  8 9.D+07 -2.438D+02 1.D+00 -1.077D+01 1.D+00 1.D+00 4.D-05 4.D-13  143C  0   0
  9 9.D+08 -2.438D+02 1.D+00 -1.077D+01 1.D+00 1.D+00 5.D-05 6.D-14  144C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 9.D+09 -2.438D+02 1.D+00 -1.077D+01 1.D+00 1.D+00 2.D-05 7.D-15  145C  0   0
 11 9.D+10 -2.438D+02 1.D+00 -1.077D+01 1.D+00 1.D+00 8.D-05 8.D-16  147C  0   0
 12 9.D+11 -2.438D+02 1.D+00 -1.077D+01 1.D+00 1.D+00 1.D+04 5.D-08  155P  0   0
 13 9.D+12 -2.438D+02 1.D+00 -1.077D+01 1.D+00 1.D+00 6.D+02 5.D-11  178P  0   0
 14 9.D+13 -2.438D+02 1.D+00 -1.077D+01 1.D+00 1.D+00 1.D+06 3.D-08  183P  0   0
 15 9.D+14 -2.438D+02 1.D+00 -1.077D+01 1.D+00 1.D+00 8.D+06 2.D-08  241P  0   0
 16 9.D+15 -2.438D+02 1.D+00 -1.077D+01 1.D+00 1.D+00 1.D+08 4.D-08  246P  0   0
 17 9.D+16 -2.438D+02 1.D+00 -1.077D+01 1.D+00 1.D+00 6.D+08 2.D-08  295P  0   0
 18 9.D+17 -2.438D+02 1.D+00 -1.077D+01 1.D+00 1.D+00 5.D+09 2.D-08  305P  0   0
 19 9.D+18 -2.438D+02 1.D+00 -1.077D+01 1.D+00 1.D+00 6.D+10 6.D-09  334P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 9.D+19 -2.438D+02 1.D+00 -1.077D+01 1.D+00 1.D+00 6.D+11 2.D-08  389P  0   0
 21 9.D+20 -2.438D+02 1.D+00 -1.077D+01 1.D+00 1.D+00 5.D+12 2.D-08  399P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.10

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   1879
 Subroutine evalg    (coded=T):    535
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  39253 (  1962 calls per constraint in average)
 Subroutine evaljac  (coded=T):   5689 (   284 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    397
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 12
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 3.2D-02
 Smallest constraints scale factor : 1.1D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -7.217D+01 4.D+00 -2.277D+00 4.D+00 4.D+00 7.D-01 2.D+00    0   0   0
  1 2.D+00 -6.957D+02 3.D+00 -2.195D+01 1.D+00 1.D+00 1.D+00 8.D-01   10C  0   0
  2 7.D+01 -2.808D+02 1.D+00 -8.861D+00 1.D+00 1.D+00 6.D-06 1.D-02   70C  0   0
  3 7.D+02 -2.789D+02 1.D+00 -8.800D+00 1.D+00 1.D+00 6.D-10 8.D-05   78C  0   0
  4 7.D+03 -2.789D+02 1.D+00 -8.800D+00 1.D+00 1.D+00 1.D-08 1.D-07   81C  0   0
  5 7.D+04 -2.789D+02 1.D+00 -8.800D+00 1.D+00 1.D+00 9.D-05 2.D-09   82C  0   0
  6 7.D+05 -2.789D+02 1.D+00 -8.800D+00 1.D+00 1.D+00 5.D-05 2.D-10   83C  0   0
  7 7.D+06 -2.789D+02 1.D+00 -8.800D+00 1.D+00 1.D+00 3.D-05 9.D-12   84C  0   0
  8 7.D+07 -2.789D+02 1.D+00 -8.800D+00 1.D+00 1.D+00 3.D-05 1.D-12   85C  0   0
  9 7.D+08 -2.789D+02 1.D+00 -8.800D+00 1.D+00 1.D+00 7.D-05 5.D-14   86C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 7.D+09 -2.789D+02 1.D+00 -8.800D+00 1.D+00 1.D+00 5.D-05 1.D-14   87C  0   0
 11 7.D+10 -2.789D+02 1.D+00 -8.800D+00 1.D+00 1.D+00 4.D-05 1.D-15   88C  0   0
 12 7.D+11 -2.789D+02 1.D+00 -8.800D+00 1.D+00 1.D+00 8.D-04 1.D-15   93P  0   0
 13 7.D+12 -2.789D+02 1.D+00 -8.800D+00 1.D+00 1.D+00 3.D+03 2.D-09  100P  0   0
 14 7.D+13 -2.789D+02 1.D+00 -8.800D+00 1.D+00 1.D+00 2.D+05 2.D-09  155P  0   0
 15 7.D+14 -2.789D+02 1.D+00 -8.800D+00 1.D+00 1.D+00 2.D+06 8.D-09  163P  0   0
 16 7.D+15 -2.789D+02 1.D+00 -8.800D+00 1.D+00 1.D+00 2.D+07 3.D-09  174P  0   0
 17 7.D+16 -2.789D+02 1.D+00 -8.800D+00 1.D+00 1.D+00 4.D+05 4.D-12  178P  0   0
 18 7.D+17 -2.789D+02 1.D+00 -8.800D+00 1.D+00 1.D+00 2.D+09 2.D-09  183P  0   0
 19 7.D+18 -2.789D+02 1.D+00 -8.800D+00 1.D+00 1.D+00 7.D+09 8.D-10  209P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 7.D+19 -2.789D+02 1.D+00 -8.800D+00 1.D+00 1.D+00 8.D+08 3.D-12  251P  0   0
 21 7.D+20 -2.789D+02 1.D+00 -8.800D+00 1.D+00 1.D+00 1.D+12 2.D-09  256P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.07

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   1219
 Subroutine evalg    (coded=T):    357
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  25373 (  1268 calls per constraint in average)
 Subroutine evaljac  (coded=T):   4277 (   213 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    254
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 13
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 3.2D-02
 Smallest constraints scale factor : 8.4D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -9.529D+01 4.D+00 -3.082D+00 4.D+00 4.D+00 1.D+00 5.D+00    0   0   0
  1 1.D+00 -9.030D+02 3.D+00 -2.921D+01 2.D+00 2.D+00 1.D+00 2.D+00   10C  0   0
  2 4.D+01 -2.729D+02 1.D+00 -8.827D+00 1.D+00 1.D+00 4.D-05 3.D-02   29C  0   0
  3 4.D+01 -2.617D+02 1.D+00 -8.464D+00 1.D+00 1.D+00 2.D-05 1.D-03   33C  0   0
  4 4.D+02 -2.622D+02 1.D+00 -8.482D+00 1.D+00 1.D+00 3.D-05 2.D-05   36C  0   0
  5 4.D+03 -2.622D+02 1.D+00 -8.482D+00 1.D+00 1.D+00 3.D-08 1.D-08   38C  0   0
  6 4.D+04 -2.622D+02 1.D+00 -8.482D+00 1.D+00 1.D+00 4.D-05 9.D-10   39C  0   0
  7 4.D+05 -2.622D+02 1.D+00 -8.482D+00 1.D+00 1.D+00 5.D-05 2.D-10   40C  0   0
  8 4.D+06 -2.622D+02 1.D+00 -8.482D+00 1.D+00 1.D+00 4.D-05 1.D-11   41C  0   0
  9 4.D+07 -2.622D+02 1.D+00 -8.482D+00 1.D+00 1.D+00 7.D-07 2.D-12   42C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 4.D+08 -2.622D+02 1.D+00 -8.482D+00 1.D+00 1.D+00 2.D-05 4.D-14   43C  0   0
 11 4.D+09 -2.622D+02 1.D+00 -8.482D+00 1.D+00 1.D+00 2.D-05 1.D-14   44C  0   0
 12 4.D+10 -2.622D+02 1.D+00 -8.482D+00 1.D+00 1.D+00 1.D-04 9.D-16   46C  0   0
 13 4.D+11 -2.622D+02 1.D+00 -8.482D+00 1.D+00 1.D+00 7.D+03 2.D-08   56P  0   0
 14 4.D+12 -2.622D+02 1.D+00 -8.482D+00 1.D+00 1.D+00 5.D-03 2.D-12   63P  0   0
 15 4.D+13 -2.622D+02 1.D+00 -8.482D+00 1.D+00 1.D+00 1.D+06 3.D-08   71P  0   0
 16 4.D+14 -2.622D+02 1.D+00 -8.482D+00 1.D+00 1.D+00 1.D+07 3.D-08   98P  0   0
 17 4.D+15 -2.622D+02 1.D+00 -8.482D+00 1.D+00 1.D+00 1.D+08 3.D-08  127P  0   0
 18 4.D+16 -2.622D+02 1.D+00 -8.482D+00 1.D+00 1.D+00 1.D+09 3.D-08  137P  0   0
 19 4.D+17 -2.622D+02 1.D+00 -8.482D+00 1.D+00 1.D+00 6.D+09 1.D-08  145P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 4.D+18 -2.622D+02 1.D+00 -8.482D+00 1.D+00 1.D+00 1.D+11 3.D-08  166P  0   0
 21 4.D+19 -2.622D+02 1.D+00 -8.482D+00 1.D+00 1.D+00 1.D+12 3.D-08  206P  0   0
 22 4.D+20 -2.622D+02 1.D+00 -8.482D+00 1.D+00 1.D+00 6.D+12 1.D-08  217P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.06

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):    891
 Subroutine evalg    (coded=T):    298
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  18360 (   918 calls per constraint in average)
 Subroutine evaljac  (coded=T):   3542 (   177 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    223
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 14
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 3.0D-02
 Smallest constraints scale factor : 6.7D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -1.027D+02 2.D+00 -3.072D+00 1.D+00 1.D+00 8.D-01 7.D-01    0   0   0
  1 2.D+01 -2.468D+02 1.D+00 -7.384D+00 1.D+00 1.D+00 6.D-01 9.D-02   10C  0   0
  2 7.D+01 -1.886D+02 1.D+00 -5.643D+00 1.D+00 1.D+00 5.D-06 1.D-02   34C  0   0
  3 7.D+02 -1.906D+02 1.D+00 -5.703D+00 1.D+00 1.D+00 2.D-05 2.D-05   45C  0   0
  4 7.D+03 -1.906D+02 1.D+00 -5.703D+00 1.D+00 1.D+00 6.D-07 5.D-09   47C  0   0
  5 7.D+04 -1.906D+02 1.D+00 -5.703D+00 1.D+00 1.D+00 2.D-05 3.D-10   48C  0   0
  6 7.D+05 -1.906D+02 1.D+00 -5.703D+00 1.D+00 1.D+00 1.D-08 2.D-11   51C  0   0
  7 7.D+06 -1.906D+02 1.D+00 -5.703D+00 1.D+00 1.D+00 1.D-05 1.D-12   52C  0   0
  8 7.D+07 -1.906D+02 1.D+00 -5.703D+00 1.D+00 1.D+00 7.D-06 2.D-13   53C  0   0
  9 7.D+08 -1.906D+02 1.D+00 -5.703D+00 1.D+00 1.D+00 8.D-05 2.D-13   53C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 7.D+09 -1.906D+02 1.D+00 -5.703D+00 1.D+00 1.D+00 2.D-05 1.D-14   54C  0   0
 11 7.D+10 -1.906D+02 1.D+00 -5.703D+00 1.D+00 1.D+00 8.D-05 1.D-15   55C  0   0
 12 7.D+11 -1.906D+02 1.D+00 -5.703D+00 1.D+00 1.D+00 8.D-05 1.D-16   60C  0   0
 13 7.D+12 -1.906D+02 1.D+00 -5.703D+00 1.D+00 1.D+00 8.D-04 1.D-16   65P  0   0
 14 7.D+13 -1.906D+02 1.D+00 -5.703D+00 1.D+00 1.D+00 2.D-02 5.D-17   69P  0   0
 15 7.D+14 -1.906D+02 1.D+00 -5.703D+00 1.D+00 1.D+00 8.D-02 1.D-16   74P  0   0
 16 7.D+15 -1.906D+02 1.D+00 -5.703D+00 1.D+00 1.D+00 6.D+07 3.D-08   80P  0   0
 17 7.D+16 -1.906D+02 1.D+00 -5.703D+00 1.D+00 1.D+00 7.D+04 9.D-13   95P  0   0
 18 7.D+17 -1.906D+02 1.D+00 -5.703D+00 1.D+00 1.D+00 3.D+09 2.D-08  100P  0   0
 19 7.D+18 -1.906D+02 1.D+00 -5.703D+00 1.D+00 1.D+00 5.D+10 3.D-08  138P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 7.D+19 -1.906D+02 1.D+00 -5.703D+00 1.D+00 1.D+00 3.D+09 1.D-10  162P  0   0
 21 7.D+20 -1.906D+02 1.D+00 -5.703D+00 1.D+00 1.D+00 7.D+11 3.D-09  166P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.04

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):    740
 Subroutine evalg    (coded=T):    247
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  15356 (   767 calls per constraint in average)
 Subroutine evaljac  (coded=T):   2707 (   135 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    166
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 15
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 5.7D-02
 Smallest constraints scale factor : 1.3D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -5.705D+01 3.D+00 -3.239D+00 1.D+00 1.D+00 1.D+00 1.D+00    0   0   0
  1 9.D+00 -4.264D+02 1.D+00 -2.421D+01 1.D+00 1.D+00 2.D+00 3.D-01   10C  0   0
  2 1.D+02 -2.440D+02 1.D+00 -1.385D+01 1.D+00 1.D+00 2.D-05 1.D-02   31C  0   0
  3 1.D+03 -2.430D+02 1.D+00 -1.380D+01 1.D+00 1.D+00 1.D-09 2.D-05   35C  0   0
  4 1.D+04 -2.430D+02 1.D+00 -1.380D+01 1.D+00 1.D+00 6.D-07 3.D-08   37C  0   0
  5 1.D+05 -2.430D+02 1.D+00 -1.380D+01 1.D+00 1.D+00 6.D-05 6.D-10   38C  0   0
  6 1.D+06 -2.430D+02 1.D+00 -1.380D+01 1.D+00 1.D+00 6.D-08 6.D-11   46C  0   0
  7 1.D+07 -2.430D+02 1.D+00 -1.380D+01 1.D+00 1.D+00 3.D-05 2.D-12   47C  0   0
  8 1.D+08 -2.430D+02 1.D+00 -1.380D+01 1.D+00 1.D+00 2.D-05 3.D-13   48C  0   0
  9 1.D+09 -2.430D+02 1.D+00 -1.380D+01 1.D+00 1.D+00 8.D-06 2.D-14   49C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 1.D+10 -2.430D+02 1.D+00 -1.380D+01 1.D+00 1.D+00 3.D-05 2.D-15   50C  0   0
 11 1.D+11 -2.430D+02 1.D+00 -1.380D+01 1.D+00 1.D+00 3.D-05 4.D-16   51C  0   0
 12 1.D+12 -2.430D+02 1.D+00 -1.380D+01 1.D+00 1.D+00 1.D-03 7.D-16   56P  0   0
 13 1.D+13 -2.430D+02 1.D+00 -1.380D+01 1.D+00 1.D+00 2.D+04 4.D-09   64P  0   0
 14 1.D+14 -2.430D+02 1.D+00 -1.380D+01 1.D+00 1.D+00 1.D+05 1.D-09   68P  0   0
 15 1.D+15 -2.430D+02 1.D+00 -1.380D+01 1.D+00 1.D+00 9.D+06 2.D-08   72P  0   0
 16 1.D+16 -2.430D+02 1.D+00 -1.380D+01 1.D+00 1.D+00 8.D+07 2.D-08   79P  0   0
 17 1.D+17 -2.430D+02 1.D+00 -1.380D+01 1.D+00 1.D+00 8.D+08 2.D-08  111P  0   0
 18 1.D+18 -2.430D+02 1.D+00 -1.380D+01 1.D+00 1.D+00 1.D+10 2.D-08  201P  0   0
 19 1.D+19 -2.430D+02 1.D+00 -1.380D+01 1.D+00 1.D+00 8.D+10 2.D-08  217P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 1.D+20 -2.430D+02 1.D+00 -1.380D+01 1.D+00 1.D+00 6.D+11 4.D-09  239P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.06

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   1146
 Subroutine evalg    (coded=T):    317
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  23478 (  1173 calls per constraint in average)
 Subroutine evaljac  (coded=T):   3598 (   179 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    237
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 16
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 4.0D-02
 Smallest constraints scale factor : 1.3D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -6.392D+01 4.D+00 -2.581D+00 4.D+00 4.D+00 1.D+00 3.D+00    0   0   0
  1 2.D+00 -6.550D+02 2.D+00 -2.645D+01 2.D+00 2.D+00 1.D+00 1.D+00   10C  0   0
  2 6.D+01 -2.445D+02 1.D+00 -9.874D+00 1.D+00 1.D+00 2.D-05 3.D-02   29C  0   0
  3 6.D+02 -2.379D+02 1.D+00 -9.608D+00 1.D+00 1.D+00 2.D-05 5.D-05   41C  0   0
  4 6.D+03 -2.379D+02 1.D+00 -9.608D+00 1.D+00 1.D+00 1.D-05 6.D-08   43C  0   0
  5 6.D+04 -2.379D+02 1.D+00 -9.608D+00 1.D+00 1.D+00 2.D-10 2.D-10   45C  0   0
  6 6.D+05 -2.379D+02 1.D+00 -9.608D+00 1.D+00 1.D+00 9.D-05 2.D-10   45C  0   0
  7 6.D+06 -2.379D+02 1.D+00 -9.608D+00 1.D+00 1.D+00 7.D-05 1.D-11   46C  0   0
  8 6.D+07 -2.379D+02 1.D+00 -9.608D+00 1.D+00 1.D+00 6.D-05 1.D-12   47C  0   0
  9 6.D+08 -2.379D+02 1.D+00 -9.608D+00 1.D+00 1.D+00 4.D-05 9.D-14   48C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 6.D+09 -2.379D+02 1.D+00 -9.608D+00 1.D+00 1.D+00 2.D-05 7.D-15   49C  0   0
 11 6.D+10 -2.379D+02 1.D+00 -9.608D+00 1.D+00 1.D+00 4.D-05 6.D-16   50C  0   0
 12 6.D+11 -2.379D+02 1.D+00 -9.608D+00 1.D+00 1.D+00 1.D-03 2.D-15   53P  0   0
 13 6.D+12 -2.379D+02 1.D+00 -9.608D+00 1.D+00 1.D+00 2.D+04 3.D-09   59P  0   0
 14 6.D+13 -2.379D+02 1.D+00 -9.608D+00 1.D+00 1.D+00 7.D+05 1.D-08   63P  0   0
 15 6.D+14 -2.379D+02 1.D+00 -9.608D+00 1.D+00 1.D+00 2.D+05 8.D-10  744P  0   0
 16 6.D+15 -2.379D+02 1.D+00 -9.608D+00 1.D+00 1.D+00 2.D+07 4.D-09  752P  0   0
 17 6.D+16 -2.379D+02 1.D+00 -9.608D+00 1.D+00 1.D+00 7.D+08 1.D-08  815P  0   0
 18 6.D+17 -2.379D+02 1.D+00 -9.608D+00 1.D+00 1.D+00 1.D+09 1.D-09  988P  0   0
 19 6.D+18 -2.379D+02 1.D+00 -9.608D+00 1.D+00 1.D+00 1.D+10 2.D-09 1024P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 6.D+19 -2.379D+02 1.D+00 -9.608D+00 1.D+00 1.D+00 1.D+11 2.D-09 1397P  0   0
 21 6.D+20 -2.379D+02 1.D+00 -9.608D+00 1.D+00 1.D+00 7.D+12 1.D-08 1446P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.32

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   7738
 Subroutine evalg    (coded=T):   1529
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T): 155355 (  7767 calls per constraint in average)
 Subroutine evaljac  (coded=T):  15214 (   760 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):   1450
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 17
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 4.5D-02
 Smallest constraints scale factor : 1.1D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -6.467D+01 4.D+00 -2.885D+00 4.D+00 4.D+00 1.D+00 2.D+00    0   0   0
  1 3.D+00 -5.996D+02 2.D+00 -2.675D+01 1.D+00 1.D+00 1.D+00 9.D-01   10C  0   0
  2 1.D+02 -2.534D+02 1.D+00 -1.131D+01 1.D+00 1.D+00 3.D-06 2.D-02   47C  0   0
  3 1.D+03 -2.494D+02 1.D+00 -1.113D+01 1.D+00 1.D+00 1.D-05 3.D-05   55C  0   0
  4 1.D+04 -2.494D+02 1.D+00 -1.113D+01 1.D+00 1.D+00 6.D-05 7.D-09   57C  0   0
  5 1.D+05 -2.494D+02 1.D+00 -1.113D+01 1.D+00 1.D+00 6.D-05 7.D-10   58C  0   0
  6 1.D+06 -2.494D+02 1.D+00 -1.113D+01 1.D+00 1.D+00 3.D-05 7.D-11   59C  0   0
  7 1.D+07 -2.494D+02 1.D+00 -1.113D+01 1.D+00 1.D+00 4.D-05 4.D-12   60C  0   0
  8 1.D+08 -2.494D+02 1.D+00 -1.113D+01 1.D+00 1.D+00 5.D-05 4.D-13   61C  0   0
  9 1.D+09 -2.494D+02 1.D+00 -1.113D+01 1.D+00 1.D+00 4.D-05 7.D-14   62C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 1.D+10 -2.494D+02 1.D+00 -1.113D+01 1.D+00 1.D+00 2.D-05 2.D-15   63C  0   0
 11 1.D+11 -2.494D+02 1.D+00 -1.113D+01 1.D+00 1.D+00 4.D-05 5.D-16   64C  0   0
 12 1.D+12 -2.494D+02 1.D+00 -1.113D+01 1.D+00 1.D+00 4.D-04 3.D-16   70P  0   0
 13 1.D+13 -2.494D+02 1.D+00 -1.113D+01 1.D+00 1.D+00 2.D+03 7.D-10   76P  0   0
 14 1.D+14 -2.494D+02 1.D+00 -1.113D+01 1.D+00 1.D+00 2.D+05 5.D-09   82P  0   0
 15 1.D+15 -2.494D+02 1.D+00 -1.113D+01 1.D+00 1.D+00 2.D+06 5.D-09   98P  0   0
 16 1.D+16 -2.494D+02 1.D+00 -1.113D+01 1.D+00 1.D+00 7.D+06 7.D-10  103P  0   0
 17 1.D+17 -2.494D+02 1.D+00 -1.113D+01 1.D+00 1.D+00 2.D+08 5.D-09  164P  0   0
 18 1.D+18 -2.494D+02 1.D+00 -1.113D+01 1.D+00 1.D+00 3.D+09 1.D-08  168P  0   0
 19 1.D+19 -2.494D+02 1.D+00 -1.113D+01 1.D+00 1.D+00 2.D+10 6.D-09  180P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 1.D+20 -2.494D+02 1.D+00 -1.113D+01 1.D+00 1.D+00 4.D+11 1.D-08  184P  0   0
 21 1.D+21 -2.494D+02 1.D+00 -1.113D+01 1.D+00 1.D+00 1.D+12 4.D-09  199P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.06

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):    978
 Subroutine evalg    (coded=T):    283
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  20213 (  1010 calls per constraint in average)
 Subroutine evaljac  (coded=T):   3262 (   163 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    197
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 18
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 4.8D-02
 Smallest constraints scale factor : 1.3D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -3.261D+01 4.D+00 -1.563D+00 4.D+00 4.D+00 7.D-01 3.D+00    0   0   0
  1 1.D+00 -1.081D+03 3.D+00 -5.184D+01 3.D+00 3.D+00 1.D+00 3.D+00   10C  0   0
  2 4.D+01 -2.759D+02 1.D+00 -1.323D+01 1.D+00 1.D+00 5.D-08 4.D-02   31C  0   0
  3 4.D+01 -2.675D+02 1.D+00 -1.282D+01 1.D+00 1.D+00 2.D-08 3.D-03   35C  0   0
  4 4.D+02 -2.676D+02 1.D+00 -1.283D+01 1.D+00 1.D+00 2.D-06 1.D-05   38C  0   0
  5 4.D+03 -2.676D+02 1.D+00 -1.283D+01 1.D+00 1.D+00 1.D-06 1.D-08   40C  0   0
  6 4.D+04 -2.676D+02 1.D+00 -1.283D+01 1.D+00 1.D+00 3.D-05 6.D-10   41C  0   0
  7 4.D+05 -2.676D+02 1.D+00 -1.283D+01 1.D+00 1.D+00 5.D-05 9.D-11   42C  0   0
  8 4.D+06 -2.676D+02 1.D+00 -1.283D+01 1.D+00 1.D+00 3.D-05 1.D-11   43C  0   0
  9 4.D+07 -2.676D+02 1.D+00 -1.283D+01 1.D+00 1.D+00 3.D-08 9.D-13   44C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 4.D+08 -2.676D+02 1.D+00 -1.283D+01 1.D+00 1.D+00 3.D-07 2.D-16   45C  0   0
 11 4.D+09 -2.676D+02 1.D+00 -1.283D+01 1.D+00 1.D+00 3.D-06 2.D-16   45C  0   0
 12 4.D+10 -2.676D+02 1.D+00 -1.283D+01 1.D+00 1.D+00 3.D-05 2.D-16   45C  0   0
 13 4.D+11 -2.676D+02 1.D+00 -1.283D+01 1.D+00 1.D+00 2.D-04 1.D-16   50P  0   0
 14 4.D+12 -2.676D+02 1.D+00 -1.283D+01 1.D+00 1.D+00 6.D+04 5.D-08   57P  0   0
 15 4.D+13 -2.676D+02 1.D+00 -1.283D+01 1.D+00 1.D+00 6.D+04 2.D-09   84P  0   0
 16 4.D+14 -2.676D+02 1.D+00 -1.283D+01 1.D+00 1.D+00 1.D+04 5.D-11  125P  0   0
 17 4.D+15 -2.676D+02 1.D+00 -1.283D+01 1.D+00 1.D+00 1.D+07 4.D-09  130P  0   0
 18 4.D+16 -2.676D+02 1.D+00 -1.283D+01 1.D+00 1.D+00 2.D+06 7.D-10  236P  0   0
 19 4.D+17 -2.676D+02 1.D+00 -1.283D+01 1.D+00 1.D+00 1.D+09 1.D-08  243P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 4.D+18 -2.676D+02 1.D+00 -1.283D+01 1.D+00 1.D+00 4.D+07 6.D-13  257P  0   0
 21 4.D+19 -2.676D+02 1.D+00 -1.283D+01 1.D+00 1.D+00 3.D+11 2.D-08  262P  0   0
 22 4.D+20 -2.676D+02 1.D+00 -1.283D+01 1.D+00 1.D+00 1.D+12 8.D-09  292P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.10

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   1584
 Subroutine evalg    (coded=T):    369
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  32150 (  1607 calls per constraint in average)
 Subroutine evaljac  (coded=T):   4396 (   219 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    290
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 19
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 2.4D-02
 Smallest constraints scale factor : 7.4D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -1.746D+02 2.D+00 -4.225D+00 1.D+00 1.D+00 7.D-01 9.D-01    0   0   0
  1 3.D+01 -1.438D+02 1.D+00 -3.480D+00 2.D-01 2.D-01 8.D-01 9.D-02   10C  0   0
  2 3.D+01 -2.095D+02 1.D+00 -5.068D+00 2.D-01 2.D-01 4.D-05 2.D-02   32C  0   0
  3 3.D+02 -1.958D+02 1.D+00 -4.737D+00 2.D-01 2.D-01 2.D-05 8.D-05   41C  0   0
  4 3.D+03 -1.958D+02 1.D+00 -4.738D+00 2.D-01 2.D-01 5.D-07 7.D-08   44C  0   0
  5 3.D+04 -1.958D+02 1.D+00 -4.738D+00 2.D-01 2.D-01 3.D-05 9.D-10   45C  0   0
  6 3.D+05 -1.958D+02 1.D+00 -4.738D+00 2.D-01 2.D-01 8.D-06 2.D-11   46C  0   0
  7 3.D+06 -1.958D+02 1.D+00 -4.738D+00 2.D-01 2.D-01 2.D-05 5.D-12   47C  0   0
  8 3.D+07 -1.958D+02 1.D+00 -4.738D+00 2.D-01 2.D-01 3.D-06 5.D-13   48C  0   0
  9 3.D+08 -1.958D+02 1.D+00 -4.738D+00 2.D-01 2.D-01 1.D-06 1.D-14   49C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 3.D+09 -1.958D+02 1.D+00 -4.738D+00 2.D-01 2.D-01 5.D-05 1.D-14   49C  0   0
 11 3.D+10 -1.958D+02 1.D+00 -4.738D+00 2.D-01 2.D-01 5.D-05 6.D-16   50C  0   0
 12 3.D+11 -1.958D+02 1.D+00 -4.738D+00 2.D-01 2.D-01 2.D-04 2.D-16   55P  0   0
 13 3.D+12 -1.958D+02 1.D+00 -4.738D+00 2.D-01 2.D-01 4.D-03 8.D-16   58P  0   0
 14 3.D+13 -1.958D+02 1.D+00 -4.738D+00 2.D-01 2.D-01 5.D-02 2.D-16   62P  0   0
 15 3.D+14 -1.958D+02 1.D+00 -4.738D+00 2.D-01 2.D-01 5.D-01 3.D-16   66P  0   0
 16 3.D+15 -1.958D+02 1.D+00 -4.738D+00 2.D-01 2.D-01 1.D+07 1.D-08   70P  0   0
 17 3.D+16 -1.958D+02 1.D+00 -4.738D+00 2.D-01 2.D-01 2.D+07 2.D-09   75P  0   0
 18 3.D+17 -1.958D+02 1.D+00 -4.738D+00 2.D-01 2.D-01 3.D+08 2.D-09   79P  0   0
 19 3.D+18 -1.958D+02 1.D+00 -4.738D+00 2.D-01 2.D-01 3.D+08 3.D-10   84P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 3.D+19 -1.958D+02 1.D+00 -4.738D+00 2.D-01 2.D-01 2.D+10 2.D-09   88P  0   0
 21 3.D+20 -1.958D+02 1.D+00 -4.738D+00 2.D-01 2.D-01 5.D+11 5.D-09  101P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.03

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):    410
 Subroutine evalg    (coded=T):    180
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):   8706 (   435 calls per constraint in average)
 Subroutine evaljac  (coded=T):   2088 (   104 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    100
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 20
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 5.8D-02
 Smallest constraints scale factor : 1.7D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -4.328D+01 4.D+00 -2.508D+00 4.D+00 4.D+00 1.D+00 5.D+00    0   0   0
  1 1.D+00 -1.864D+03 5.D+00 -1.080D+02 5.D+00 5.D+00 2.D+00 5.D+00   10C  0   0
  2 3.D+01 -3.080D+02 1.D+00 -1.785D+01 1.D+00 1.D+00 2.D-06 4.D-02   38C  0   0
  3 3.D+01 -3.051D+02 1.D+00 -1.768D+01 1.D+00 1.D+00 4.D-09 8.D-02   56C  0   0
  4 3.D+02 -2.978D+02 1.D+00 -1.725D+01 1.D+00 1.D+00 6.D-08 3.D-03   87C  0   0
  5 3.D+03 -2.978D+02 1.D+00 -1.725D+01 1.D+00 1.D+00 3.D-07 3.D-05   96C  0   0
  6 3.D+04 -2.978D+02 1.D+00 -1.725D+01 1.D+00 1.D+00 2.D-08 3.D-08   99C  0   0
  7 3.D+05 -2.978D+02 1.D+00 -1.725D+01 1.D+00 1.D+00 6.D-05 2.D-10  100C  0   0
  8 3.D+06 -2.978D+02 1.D+00 -1.725D+01 1.D+00 1.D+00 3.D-05 3.D-11  101C  0   0
  9 3.D+07 -2.978D+02 1.D+00 -1.725D+01 1.D+00 1.D+00 2.D-05 8.D-13  102C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 3.D+08 -2.978D+02 1.D+00 -1.725D+01 1.D+00 1.D+00 1.D-05 1.D-13  103C  0   0
 11 3.D+09 -2.978D+02 1.D+00 -1.725D+01 1.D+00 1.D+00 2.D-05 6.D-15  104C  0   0
 12 3.D+10 -2.978D+02 1.D+00 -1.725D+01 1.D+00 1.D+00 9.D-05 1.D-15  105C  0   0
 13 3.D+11 -2.978D+02 1.D+00 -1.725D+01 1.D+00 1.D+00 1.D-03 5.D-15  111P  0   0
 14 3.D+12 -2.978D+02 1.D+00 -1.725D+01 1.D+00 1.D+00 8.D-03 3.D-15  116P  0   0
 15 3.D+13 -2.978D+02 1.D+00 -1.725D+01 1.D+00 1.D+00 1.D+06 4.D-08  122P  0   0
 16 3.D+14 -2.978D+02 1.D+00 -1.725D+01 1.D+00 1.D+00 4.D+06 1.D-08  257P  0   0
 17 3.D+15 -2.978D+02 1.D+00 -1.725D+01 1.D+00 1.D+00 3.D+07 1.D-08  262P  0   0
 18 3.D+16 -2.978D+02 1.D+00 -1.725D+01 1.D+00 1.D+00 8.D+08 3.D-08  357P  0   0
 19 3.D+17 -2.978D+02 1.D+00 -1.725D+01 1.D+00 1.D+00 1.D+09 4.D-09  447P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 3.D+18 -2.978D+02 1.D+00 -1.725D+01 1.D+00 1.D+00 4.D+10 1.D-08  472P  0   0
 21 3.D+19 -2.978D+02 1.D+00 -1.725D+01 1.D+00 1.D+00 2.D+07 2.D-12  494P  0   0
 22 3.D+20 -2.978D+02 1.D+00 -1.725D+01 1.D+00 1.D+00 1.D+12 5.D-09  514P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.13

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   2504
 Subroutine evalg    (coded=T):    626
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  51215 (  2560 calls per constraint in average)
 Subroutine evaljac  (coded=T):   7739 (   386 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    513
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 21
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 4.9D-02
 Smallest constraints scale factor : 1.4D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -3.849D+01 4.D+00 -1.881D+00 4.D+00 4.D+00 7.D-01 4.D+00    0   0   0
  1 1.D+00 -1.152D+03 3.D+00 -5.630D+01 3.D+00 3.D+00 1.D+00 3.D+00   10C  0   0
  2 3.D+01 -2.914D+02 1.D+00 -1.424D+01 1.D+00 1.D+00 1.D-04 6.D-02   36C  0   0
  3 3.D+01 -2.820D+02 1.D+00 -1.379D+01 1.D+00 1.D+00 4.D-07 6.D-02   49C  0   0
  4 3.D+02 -2.793D+02 1.D+00 -1.365D+01 1.D+00 1.D+00 9.D-05 5.D-03   72C  0   0
  5 3.D+03 -2.789D+02 1.D+00 -1.363D+01 1.D+00 1.D+00 5.D-07 2.D-05   79C  0   0
  6 3.D+04 -2.789D+02 1.D+00 -1.363D+01 1.D+00 1.D+00 1.D-07 7.D-09   83C  0   0
  7 3.D+05 -2.789D+02 1.D+00 -1.363D+01 1.D+00 1.D+00 1.D-05 9.D-11   84C  0   0
  8 3.D+06 -2.789D+02 1.D+00 -1.363D+01 1.D+00 1.D+00 5.D-06 4.D-12   85C  0   0
  9 3.D+07 -2.789D+02 1.D+00 -1.363D+01 1.D+00 1.D+00 2.D-05 7.D-13   86C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 3.D+08 -2.789D+02 1.D+00 -1.363D+01 1.D+00 1.D+00 2.D-06 3.D-14   87C  0   0
 11 3.D+09 -2.789D+02 1.D+00 -1.363D+01 1.D+00 1.D+00 1.D-05 3.D-15   88C  0   0
 12 3.D+10 -2.789D+02 1.D+00 -1.363D+01 1.D+00 1.D+00 1.D-05 6.D-16   89C  0   0
 13 3.D+11 -2.789D+02 1.D+00 -1.363D+01 1.D+00 1.D+00 5.D-05 1.D-16   90C  0   0
 14 3.D+12 -2.789D+02 1.D+00 -1.363D+01 1.D+00 1.D+00 5.D-04 2.D-16   96P  0   0
 15 3.D+13 -2.789D+02 1.D+00 -1.363D+01 1.D+00 1.D+00 4.D-03 1.D-16  100P  0   0
 16 3.D+14 -2.789D+02 1.D+00 -1.363D+01 1.D+00 1.D+00 4.D-02 1.D-16  105P  0   0
 17 3.D+15 -2.789D+02 1.D+00 -1.363D+01 1.D+00 1.D+00 4.D-01 1.D-16  108P  0   0
 18 3.D+16 -2.789D+02 1.D+00 -1.363D+01 1.D+00 1.D+00 4.D+08 1.D-08  112P  0   0
 19 3.D+17 -2.789D+02 1.D+00 -1.363D+01 1.D+00 1.D+00 9.D+08 5.D-09  117P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 3.D+18 -2.789D+02 1.D+00 -1.363D+01 1.D+00 1.D+00 4.D+09 3.D-09  127P  0   0
 21 3.D+19 -2.789D+02 1.D+00 -1.363D+01 1.D+00 1.D+00 3.D+10 2.D-09  134P  0   0
 22 3.D+20 -2.789D+02 1.D+00 -1.363D+01 1.D+00 1.D+00 4.D+11 3.D-09  142P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.03

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):    451
 Subroutine evalg    (coded=T):    230
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):   9695 (   484 calls per constraint in average)
 Subroutine evaljac  (coded=T):   2817 (   140 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    140
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 22
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 6.5D-02
 Smallest constraints scale factor : 1.6D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -2.165D+01 4.D+00 -1.397D+00 3.D+00 3.D+00 6.D-01 4.D+00    0   0   0
  1 1.D+00 -1.950D+03 6.D+00 -1.258D+02 6.D+00 6.D+00 1.D+00 7.D+00   10C  0   0
  2 2.D+01 -2.954D+02 1.D+00 -1.906D+01 1.D+00 1.D+00 9.D-05 1.D-01   40C  0   0
  3 2.D+01 -2.908D+02 1.D+00 -1.876D+01 1.D+00 1.D+00 2.D-06 1.D-01   62C  0   0
  4 2.D+02 -2.798D+02 1.D+00 -1.805D+01 1.D+00 1.D+00 4.D-06 1.D-02  125C  0   0
  5 2.D+03 -2.789D+02 1.D+00 -1.799D+01 1.D+00 1.D+00 1.D-06 5.D-05  145C  0   0
  6 2.D+04 -2.789D+02 1.D+00 -1.799D+01 1.D+00 1.D+00 7.D-08 4.D-08  148C  0   0
  7 2.D+05 -2.789D+02 1.D+00 -1.799D+01 1.D+00 1.D+00 6.D-08 2.D-12  150C  0   0
  8 2.D+06 -2.789D+02 1.D+00 -1.799D+01 1.D+00 1.D+00 5.D-06 2.D-12  150C  0   0
  9 2.D+07 -2.789D+02 1.D+00 -1.799D+01 1.D+00 1.D+00 5.D-05 2.D-12  150C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 2.D+08 -2.789D+02 1.D+00 -1.799D+01 1.D+00 1.D+00 4.D-05 3.D-13  151C  0   0
 11 2.D+09 -2.789D+02 1.D+00 -1.799D+01 1.D+00 1.D+00 3.D-05 8.D-15  152C  0   0
 12 2.D+10 -2.789D+02 1.D+00 -1.799D+01 1.D+00 1.D+00 4.D-05 8.D-16  153C  0   0
 13 2.D+11 -2.789D+02 1.D+00 -1.799D+01 1.D+00 1.D+00 8.D-05 5.D-16  157C  0   0
 14 2.D+12 -2.789D+02 1.D+00 -1.799D+01 1.D+00 1.D+00 1.D-02 8.D-16  160P  0   0
 15 2.D+13 -2.789D+02 1.D+00 -1.799D+01 1.D+00 1.D+00 2.D-02 8.D-16  168P  0   0
 16 2.D+14 -2.789D+02 1.D+00 -1.799D+01 1.D+00 1.D+00 2.D-01 8.D-16  172P  0   0
 17 2.D+15 -2.789D+02 1.D+00 -1.799D+01 1.D+00 1.D+00 1.D+07 1.D-08  177P  0   0
 18 2.D+16 -2.789D+02 1.D+00 -1.799D+01 1.D+00 1.D+00 3.D+06 1.D-10  374P  0   0
 19 2.D+17 -2.789D+02 1.D+00 -1.799D+01 1.D+00 1.D+00 2.D+08 1.D-09  379P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 2.D+18 -2.789D+02 1.D+00 -1.799D+01 1.D+00 1.D+00 7.D+08 2.D-10  420P  0   0
 21 2.D+19 -2.789D+02 1.D+00 -1.799D+01 1.D+00 1.D+00 4.D+11 2.D-08  436P  0   0
 22 2.D+20 -2.789D+02 1.D+00 -1.799D+01 1.D+00 1.D+00 5.D+12 2.D-08  558P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.15

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   2550
 Subroutine evalg    (coded=T):    683
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  52419 (  2620 calls per constraint in average)
 Subroutine evaljac  (coded=T):   7921 (   396 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    557
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 23
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 3.2D-02
 Smallest constraints scale factor : 1.2D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -6.007D+01 3.D+00 -1.929D+00 2.D+00 2.D+00 6.D-01 2.D+00    0   0   0
  1 3.D+00 -4.931D+02 1.D+00 -1.583D+01 1.D+00 1.D+00 1.D+00 6.D-01   10C  0   0
  2 7.D+01 -2.534D+02 1.D+00 -8.136D+00 1.D+00 1.D+00 9.D-06 1.D-02   77C  0   0
  3 7.D+02 -2.494D+02 1.D+00 -8.007D+00 1.D+00 1.D+00 6.D-05 2.D-05   84C  0   0
  4 7.D+03 -2.494D+02 1.D+00 -8.007D+00 1.D+00 1.D+00 5.D-05 5.D-08   86C  0   0
  5 7.D+04 -2.494D+02 1.D+00 -8.007D+00 1.D+00 1.D+00 4.D-09 7.D-10   88C  0   0
  6 7.D+05 -2.494D+02 1.D+00 -8.007D+00 1.D+00 1.D+00 2.D-05 3.D-11   89C  0   0
  7 7.D+06 -2.494D+02 1.D+00 -8.007D+00 1.D+00 1.D+00 1.D-06 2.D-12   90C  0   0
  8 7.D+07 -2.494D+02 1.D+00 -8.007D+00 1.D+00 1.D+00 1.D-06 1.D-14   91C  0   0
  9 7.D+08 -2.494D+02 1.D+00 -8.007D+00 1.D+00 1.D+00 1.D-05 1.D-14   91C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 7.D+09 -2.494D+02 1.D+00 -8.007D+00 1.D+00 1.D+00 1.D-05 2.D-15   92C  0   0
 11 7.D+10 -2.494D+02 1.D+00 -8.007D+00 1.D+00 1.D+00 4.D-05 7.D-16   93C  0   0
 12 7.D+11 -2.494D+02 1.D+00 -8.007D+00 1.D+00 1.D+00 5.D-04 4.D-16   99P  0   0
 13 7.D+12 -2.494D+02 1.D+00 -8.007D+00 1.D+00 1.D+00 2.D+02 8.D-11  106P  0   0
 14 7.D+13 -2.494D+02 1.D+00 -8.007D+00 1.D+00 1.D+00 1.D+06 2.D-08  111P  0   0
 15 7.D+14 -2.494D+02 1.D+00 -8.007D+00 1.D+00 1.D+00 3.D+05 1.D-09 1111M  0   0
 16 7.D+15 -2.494D+02 1.D+00 -8.007D+00 1.D+00 1.D+00 7.D+07 9.D-09 1115P  0   0
 17 7.D+16 -2.494D+02 1.D+00 -8.007D+00 1.D+00 1.D+00 1.D+07 2.D-09 1541P  0   0
 18 7.D+17 -2.494D+02 1.D+00 -8.007D+00 1.D+00 1.D+00 1.D+10 4.D-08 1545P  0   0
 19 7.D+18 -2.494D+02 1.D+00 -8.007D+00 1.D+00 1.D+00 3.D+10 7.D-09 1560P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 7.D+19 -2.494D+02 1.D+00 -8.007D+00 1.D+00 1.D+00 3.D+11 4.D-09 1569P  0   0
 21 7.D+20 -2.494D+02 1.D+00 -8.007D+00 1.D+00 1.D+00 3.D+12 1.D-08 1595P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.44

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   9261
 Subroutine evalg    (coded=T):   1696
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T): 186193 (  9309 calls per constraint in average)
 Subroutine evaljac  (coded=T):  19451 (   972 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):   1593
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 24
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 6.0D-02
 Smallest constraints scale factor : 2.0D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -2.213D+01 4.D+00 -1.320D+00 4.D+00 4.D+00 9.D-01 7.D+00    0   0   0
  1 3.D-01 -6.975D+03 2.D+01 -4.161D+02 2.D+01 2.D+01 2.D-01 5.D+01   10C  0   0
  2 6.D+00 -3.463D+02 1.D+00 -2.066D+01 1.D+00 1.D+00 7.D-06 2.D-01   54C  0   0
  3 6.D+00 -3.490D+02 1.D+00 -2.082D+01 1.D+00 1.D+00 7.D-08 4.D-01   71C  0   0
  4 6.D+01 -3.016D+02 1.D+00 -1.799D+01 1.D+00 1.D+00 7.D-06 5.D-02   92C  0   0
  5 6.D+02 -2.978D+02 1.D+00 -1.776D+01 1.D+00 1.D+00 8.D-05 6.D-04  101C  0   0
  6 6.D+03 -2.978D+02 1.D+00 -1.776D+01 1.D+00 1.D+00 4.D-06 3.D-06  105C  0   0
  7 6.D+04 -2.978D+02 1.D+00 -1.776D+01 1.D+00 1.D+00 4.D-05 2.D-09  107C  0   0
  8 6.D+05 -2.978D+02 1.D+00 -1.776D+01 1.D+00 1.D+00 8.D-06 8.D-11  108C  0   0
  9 6.D+06 -2.978D+02 1.D+00 -1.776D+01 1.D+00 1.D+00 4.D-05 7.D-12  109C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 6.D+07 -2.978D+02 1.D+00 -1.776D+01 1.D+00 1.D+00 3.D-05 1.D-12  110C  0   0
 11 6.D+08 -2.978D+02 1.D+00 -1.776D+01 1.D+00 1.D+00 3.D-05 6.D-14  111C  0   0
 12 6.D+09 -2.978D+02 1.D+00 -1.776D+01 1.D+00 1.D+00 3.D-05 5.D-15  112C  0   0
 13 6.D+10 -2.978D+02 1.D+00 -1.776D+01 1.D+00 1.D+00 7.D-05 1.D-15  113C  0   0
 14 6.D+11 -2.978D+02 1.D+00 -1.776D+01 1.D+00 1.D+00 9.D-05 2.D-16  117C  0   0
 15 6.D+12 -2.978D+02 1.D+00 -1.776D+01 1.D+00 1.D+00 1.D-02 3.D-15  120P  0   0
 16 6.D+13 -2.978D+02 1.D+00 -1.776D+01 1.D+00 1.D+00 6.D+05 1.D-08  126P  0   0
 17 6.D+14 -2.978D+02 1.D+00 -1.776D+01 1.D+00 1.D+00 8.D+05 9.D-10 1126M  0   0
 18 6.D+15 -2.978D+02 1.D+00 -1.776D+01 1.D+00 1.D+00 6.D+07 1.D-08 1131P  0   0
 19 6.D+16 -2.978D+02 1.D+00 -1.776D+01 1.D+00 1.D+00 8.D+08 1.D-08 1144P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 6.D+17 -2.978D+02 1.D+00 -1.776D+01 1.D+00 1.D+00 8.D+09 1.D-08 1149P  0   0
 21 6.D+18 -2.978D+02 1.D+00 -1.776D+01 1.D+00 1.D+00 9.D+10 1.D-08 1167P  0   0
 22 6.D+19 -2.978D+02 1.D+00 -1.776D+01 1.D+00 1.D+00 1.D+11 2.D-09 1172P  0   0
 23 6.D+20 -2.978D+02 1.D+00 -1.776D+01 1.D+00 1.D+00 1.D+13 2.D-08 1177P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.23

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   6052
 Subroutine evalg    (coded=T):   1282
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T): 122028 (  6101 calls per constraint in average)
 Subroutine evaljac  (coded=T):  14246 (   712 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):   1175
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 25
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 2.8D-02
 Smallest constraints scale factor : 7.5D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -7.854D+01 3.D+00 -2.238D+00 3.D+00 3.D+00 7.D-01 3.D+00    0   0   0
  1 3.D+00 -3.344D+02 2.D+00 -9.528D+00 1.D+00 1.D+00 1.D+00 9.D-01   10C  0   0
  2 6.D+01 -1.979D+02 1.D+00 -5.637D+00 1.D+00 1.D+00 2.D-05 2.D-02   46C  0   0
  3 6.D+02 -1.958D+02 1.D+00 -5.579D+00 1.D+00 1.D+00 1.D-04 6.D-05   54C  0   0
  4 6.D+03 -1.958D+02 1.D+00 -5.579D+00 1.D+00 1.D+00 1.D-07 4.D-08   57C  0   0
  5 6.D+04 -1.958D+02 1.D+00 -5.579D+00 1.D+00 1.D+00 7.D-05 1.D-09   58C  0   0
  6 6.D+05 -1.958D+02 1.D+00 -5.579D+00 1.D+00 1.D+00 5.D-05 1.D-10   59C  0   0
  7 6.D+06 -1.958D+02 1.D+00 -5.579D+00 1.D+00 1.D+00 8.D-05 2.D-11   60C  0   0
  8 6.D+07 -1.958D+02 1.D+00 -5.579D+00 1.D+00 1.D+00 8.D-05 1.D-12   61C  0   0
  9 6.D+08 -1.958D+02 1.D+00 -5.579D+00 1.D+00 1.D+00 2.D-05 3.D-13   62C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 6.D+09 -1.958D+02 1.D+00 -5.579D+00 1.D+00 1.D+00 6.D-05 1.D-14   63C  0   0
 11 6.D+10 -1.958D+02 1.D+00 -5.579D+00 1.D+00 1.D+00 6.D-05 1.D-15   64C  0   0
 12 6.D+11 -1.958D+02 1.D+00 -5.579D+00 1.D+00 1.D+00 9.D-04 1.D-16   70P  0   0
 13 6.D+12 -1.958D+02 1.D+00 -5.579D+00 1.D+00 1.D+00 5.D-03 4.D-16   77P  0   0
 14 6.D+13 -1.958D+02 1.D+00 -5.579D+00 1.D+00 1.D+00 7.D-02 1.D-15   80P  0   0
 15 6.D+14 -1.958D+02 1.D+00 -5.579D+00 1.D+00 1.D+00 3.D+06 1.D-08   85P  0   0
 16 6.D+15 -1.958D+02 1.D+00 -5.579D+00 1.D+00 1.D+00 5.D+07 3.D-08  198P  0   0
 17 6.D+16 -1.958D+02 1.D+00 -5.579D+00 1.D+00 1.D+00 2.D+08 2.D-08  203P  0   0
 18 6.D+17 -1.958D+02 1.D+00 -5.579D+00 1.D+00 1.D+00 6.D+09 3.D-08  208P  0   0
 19 6.D+18 -1.958D+02 1.D+00 -5.579D+00 1.D+00 1.D+00 3.D+10 2.D-08  414P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 6.D+19 -1.958D+02 1.D+00 -5.579D+00 1.D+00 1.D+00 4.D+11 2.D-08  445P  0   0
 21 6.D+20 -1.958D+02 1.D+00 -5.579D+00 1.D+00 1.D+00 4.D+12 3.D-08  515P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.16

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   2514
 Subroutine evalg    (coded=T):    602
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  50968 (  2548 calls per constraint in average)
 Subroutine evaljac  (coded=T):   6260 (   313 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    514
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 26
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 4.3D-02
 Smallest constraints scale factor : 1.0D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -7.403D+01 4.D+00 -3.152D+00 4.D+00 4.D+00 1.D+00 3.D+00    0   0   0
  1 3.D+00 -6.565D+02 1.D+00 -2.795D+01 1.D+00 1.D+00 1.D+00 1.D+00   10C  0   0
  2 7.D+01 -2.419D+02 1.D+00 -1.030D+01 1.D+00 1.D+00 3.D-10 3.D-02   38C  0   0
  3 7.D+02 -2.495D+02 1.D+00 -1.062D+01 1.D+00 1.D+00 9.D-05 2.D-03  225C  0   0
  4 7.D+03 -2.494D+02 1.D+00 -1.062D+01 1.D+00 1.D+00 5.D-05 1.D-06  233C  0   0
  5 7.D+04 -2.494D+02 1.D+00 -1.062D+01 1.D+00 1.D+00 1.D-07 8.D-10  235C  0   0
  6 7.D+05 -2.494D+02 1.D+00 -1.062D+01 1.D+00 1.D+00 7.D-06 1.D-11  236C  0   0
  7 7.D+06 -2.494D+02 1.D+00 -1.062D+01 1.D+00 1.D+00 8.D-05 1.D-11  236C  0   0
  8 7.D+07 -2.494D+02 1.D+00 -1.062D+01 1.D+00 1.D+00 4.D-05 1.D-12  237C  0   0
  9 7.D+08 -2.494D+02 1.D+00 -1.062D+01 1.D+00 1.D+00 9.D-05 1.D-13  238C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 7.D+09 -2.494D+02 1.D+00 -1.062D+01 1.D+00 1.D+00 7.D-05 2.D-14  239C  0   0
 11 7.D+10 -2.494D+02 1.D+00 -1.062D+01 1.D+00 1.D+00 9.D-05 1.D-15  243C  0   0
 12 7.D+11 -2.494D+02 1.D+00 -1.062D+01 1.D+00 1.D+00 9.D-05 1.D-16  247P  0   0
 13 7.D+12 -2.494D+02 1.D+00 -1.062D+01 1.D+00 1.D+00 1.D+05 5.D-08  253P  0   0
 14 7.D+13 -2.494D+02 1.D+00 -1.062D+01 1.D+00 1.D+00 1.D+05 4.D-10  262P  0   0
 15 7.D+14 -2.494D+02 1.D+00 -1.062D+01 1.D+00 1.D+00 6.D+03 3.D-11  278P  0   0
 16 7.D+15 -2.494D+02 1.D+00 -1.062D+01 1.D+00 1.D+00 8.D+06 4.D-09  282P  0   0
 17 7.D+16 -2.494D+02 1.D+00 -1.062D+01 1.D+00 1.D+00 4.D+05 8.D-11  316P  0   0
 18 7.D+17 -2.494D+02 1.D+00 -1.062D+01 1.D+00 1.D+00 4.D+09 2.D-08  322P  0   0
 19 7.D+18 -2.494D+02 1.D+00 -1.062D+01 1.D+00 1.D+00 5.D+08 3.D-10  344P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 7.D+19 -2.494D+02 1.D+00 -1.062D+01 1.D+00 1.D+00 2.D+11 3.D-09  352P  0   0
 21 7.D+20 -2.494D+02 1.D+00 -1.062D+01 1.D+00 1.D+00 4.D+12 2.D-08  371P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.08

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   1664
 Subroutine evalg    (coded=T):    577
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  36362 (  1818 calls per constraint in average)
 Subroutine evaljac  (coded=T):   6553 (   327 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    369
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 27
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 5.8D-02
 Smallest constraints scale factor : 1.4D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -2.518D+01 4.D+00 -1.461D+00 4.D+00 4.D+00 6.D-01 3.D+00    0   0   0
  1 9.D-01 -1.245D+03 4.D+00 -7.221D+01 4.D+00 4.D+00 1.D+00 4.D+00   10C  0   0
  2 2.D+01 -2.882D+02 1.D+00 -1.672D+01 1.D+00 1.D+00 1.D-06 8.D-02   49C  0   0
  3 2.D+01 -2.491D+02 1.D+00 -1.445D+01 1.D+00 1.D+00 9.D-09 3.D-02   55C  0   0
  4 2.D+02 -2.494D+02 1.D+00 -1.447D+01 1.D+00 1.D+00 1.D-05 2.D-04   60C  0   0
  5 2.D+03 -2.494D+02 1.D+00 -1.447D+01 1.D+00 1.D+00 9.D-09 8.D-07   63C  0   0
  6 2.D+04 -2.494D+02 1.D+00 -1.447D+01 1.D+00 1.D+00 7.D-09 5.D-11   65C  0   0
  7 2.D+05 -2.494D+02 1.D+00 -1.447D+01 1.D+00 1.D+00 3.D-05 5.D-11   65C  0   0
  8 2.D+06 -2.494D+02 1.D+00 -1.447D+01 1.D+00 1.D+00 1.D-05 2.D-11   66C  0   0
  9 2.D+07 -2.494D+02 1.D+00 -1.447D+01 1.D+00 1.D+00 2.D-05 9.D-13   67C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 2.D+08 -2.494D+02 1.D+00 -1.447D+01 1.D+00 1.D+00 9.D-06 7.D-14   68C  0   0
 11 2.D+09 -2.494D+02 1.D+00 -1.447D+01 1.D+00 1.D+00 9.D-06 8.D-15   69C  0   0
 12 2.D+10 -2.494D+02 1.D+00 -1.447D+01 1.D+00 1.D+00 5.D-05 4.D-16   70C  0   0
 13 2.D+11 -2.494D+02 1.D+00 -1.447D+01 1.D+00 1.D+00 9.D-05 4.D-16   74C  0   0
 14 2.D+12 -2.494D+02 1.D+00 -1.447D+01 1.D+00 1.D+00 1.D-03 4.D-16   77P  0   0
 15 2.D+13 -2.494D+02 1.D+00 -1.447D+01 1.D+00 1.D+00 1.D-02 4.D-16   80P  0   0
 16 2.D+14 -2.494D+02 1.D+00 -1.447D+01 1.D+00 1.D+00 9.D+05 1.D-08   86P  0   0
 17 2.D+15 -2.494D+02 1.D+00 -1.447D+01 1.D+00 1.D+00 9.D+06 1.D-08  552P  0   0
 18 2.D+16 -2.494D+02 1.D+00 -1.447D+01 1.D+00 1.D+00 1.D+05 6.D-13  557P  0   0
 19 2.D+17 -2.494D+02 1.D+00 -1.447D+01 1.D+00 1.D+00 5.D+08 7.D-09  562P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 2.D+18 -2.494D+02 1.D+00 -1.447D+01 1.D+00 1.D+00 4.D+09 5.D-09  572P  0   0
 21 2.D+19 -2.494D+02 1.D+00 -1.447D+01 1.D+00 1.D+00 8.D+10 1.D-08  628P  0   0
 22 2.D+20 -2.494D+02 1.D+00 -1.447D+01 1.D+00 1.D+00 5.D+11 6.D-09  633P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.12

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   3508
 Subroutine evalg    (coded=T):    723
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  70906 (  3545 calls per constraint in average)
 Subroutine evaljac  (coded=T):   7258 (   362 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    630
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 28
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 4.4D-02
 Smallest constraints scale factor : 1.3D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -6.504D+01 3.D+00 -2.871D+00 2.D+00 2.D+00 1.D+00 3.D+00    0   0   0
  1 3.D+00 -4.714D+02 2.D+00 -2.081D+01 2.D+00 2.D+00 1.D+00 1.D+00   10C  0   0
  2 6.D+01 -2.565D+02 1.D+00 -1.132D+01 1.D+00 1.D+00 5.D-05 2.D-02   82C  0   0
  3 6.D+02 -2.494D+02 1.D+00 -1.101D+01 1.D+00 1.D+00 4.D-05 5.D-05   91C  0   0
  4 6.D+03 -2.494D+02 1.D+00 -1.101D+01 1.D+00 1.D+00 1.D-08 2.D-08   94C  0   0
  5 6.D+04 -2.494D+02 1.D+00 -1.101D+01 1.D+00 1.D+00 2.D-05 5.D-10   95C  0   0
  6 6.D+05 -2.494D+02 1.D+00 -1.101D+01 1.D+00 1.D+00 2.D-05 3.D-11   96C  0   0
  7 6.D+06 -2.494D+02 1.D+00 -1.101D+01 1.D+00 1.D+00 3.D-05 4.D-12   98C  0   0
  8 6.D+07 -2.494D+02 1.D+00 -1.101D+01 1.D+00 1.D+00 3.D-05 1.D-12   99C  0   0
  9 6.D+08 -2.494D+02 1.D+00 -1.101D+01 1.D+00 1.D+00 9.D-07 5.D-14  100C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 6.D+09 -2.494D+02 1.D+00 -1.101D+01 1.D+00 1.D+00 1.D-05 3.D-15  101C  0   0
 11 6.D+10 -2.494D+02 1.D+00 -1.101D+01 1.D+00 1.D+00 8.D-05 4.D-16  102C  0   0
 12 6.D+11 -2.494D+02 1.D+00 -1.101D+01 1.D+00 1.D+00 1.D-03 1.D-16  108P  0   0
 13 6.D+12 -2.494D+02 1.D+00 -1.101D+01 1.D+00 1.D+00 1.D+05 5.D-08  116P  0   0
 14 6.D+13 -2.494D+02 1.D+00 -1.101D+01 1.D+00 1.D+00 2.D+04 7.D-10  128P  0   0
 15 6.D+14 -2.494D+02 1.D+00 -1.101D+01 1.D+00 1.D+00 5.D+06 3.D-08  132P  0   0
 16 6.D+15 -2.494D+02 1.D+00 -1.101D+01 1.D+00 1.D+00 1.D+07 7.D-09  143P  0   0
 17 6.D+16 -2.494D+02 1.D+00 -1.101D+01 1.D+00 1.D+00 3.D+08 2.D-08  154P  0   0
 18 6.D+17 -2.494D+02 1.D+00 -1.101D+01 1.D+00 1.D+00 4.D+09 6.D-09  173P  0   0
 19 6.D+18 -2.494D+02 1.D+00 -1.101D+01 1.D+00 1.D+00 5.D+08 7.D-10  336P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 6.D+19 -2.494D+02 1.D+00 -1.101D+01 1.D+00 1.D+00 3.D+11 2.D-08  346P  0   0
 21 6.D+20 -2.494D+02 1.D+00 -1.101D+01 1.D+00 1.D+00 3.D+12 2.D-08  367P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.10

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   1894
 Subroutine evalg    (coded=T):    470
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  38888 (  1944 calls per constraint in average)
 Subroutine evaljac  (coded=T):   5220 (   261 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    364
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 29
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 2.3D-02
 Smallest constraints scale factor : 7.6D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -1.239D+02 3.D+00 -2.880D+00 1.D+00 1.D+00 9.D-01 1.D+00    0   0   0
  1 1.D+01 -2.145D+02 1.D+00 -4.987D+00 1.D+00 1.D+00 3.D-01 1.D-01   10C  0   0
  2 5.D+01 -1.939D+02 1.D+00 -4.508D+00 1.D+00 1.D+00 2.D-05 1.D-02   30C  0   0
  3 5.D+02 -1.906D+02 1.D+00 -4.432D+00 1.D+00 1.D+00 5.D-06 2.D-05   51C  0   0
  4 5.D+03 -1.906D+02 1.D+00 -4.432D+00 1.D+00 1.D+00 7.D-07 1.D-08   53C  0   0
  5 5.D+04 -1.906D+02 1.D+00 -4.432D+00 1.D+00 1.D+00 6.D-05 3.D-10   54C  0   0
  6 5.D+05 -1.906D+02 1.D+00 -4.432D+00 1.D+00 1.D+00 3.D-05 2.D-10   55C  0   0
  7 5.D+06 -1.906D+02 1.D+00 -4.432D+00 1.D+00 1.D+00 2.D-05 2.D-12   56C  0   0
  8 5.D+07 -1.906D+02 1.D+00 -4.432D+00 1.D+00 1.D+00 2.D-06 3.D-13   57C  0   0
  9 5.D+08 -1.906D+02 1.D+00 -4.432D+00 1.D+00 1.D+00 7.D-06 3.D-14   58C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 5.D+09 -1.906D+02 1.D+00 -4.432D+00 1.D+00 1.D+00 7.D-05 3.D-14   58C  0   0
 11 5.D+10 -1.906D+02 1.D+00 -4.432D+00 1.D+00 1.D+00 5.D-06 1.D-15   59C  0   0
 12 5.D+11 -1.906D+02 1.D+00 -4.432D+00 1.D+00 1.D+00 4.D-05 8.D-17   65C  0   0
 13 5.D+12 -1.906D+02 1.D+00 -4.432D+00 1.D+00 1.D+00 3.D+04 6.D-09   86P  0   0
 14 5.D+13 -1.906D+02 1.D+00 -4.432D+00 1.D+00 1.D+00 1.D+03 6.D-10   99P  0   0
 15 5.D+14 -1.906D+02 1.D+00 -4.432D+00 1.D+00 1.D+00 1.D+06 3.D-09  129P  0   0
 16 5.D+15 -1.906D+02 1.D+00 -4.432D+00 1.D+00 1.D+00 4.D+07 3.D-08  170P  0   0
 17 5.D+16 -1.906D+02 1.D+00 -4.432D+00 1.D+00 1.D+00 2.D+08 1.D-08  175P  0   0
 18 5.D+17 -1.906D+02 1.D+00 -4.432D+00 1.D+00 1.D+00 3.D+09 2.D-08  268P  0   0
 19 5.D+18 -1.906D+02 1.D+00 -4.432D+00 1.D+00 1.D+00 4.D+06 8.D-13  295P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 5.D+19 -1.906D+02 1.D+00 -4.432D+00 1.D+00 1.D+00 1.D+11 8.D-09  301P  0   0
 21 5.D+20 -1.906D+02 1.D+00 -4.432D+00 1.D+00 1.D+00 1.D+12 2.D-09  349P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.10

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   1808
 Subroutine evalg    (coded=T):    432
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  36766 (  1838 calls per constraint in average)
 Subroutine evaljac  (coded=T):   4723 (   236 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    347
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 30
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 2.9D-02
 Smallest constraints scale factor : 8.5D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -6.221D+01 2.D+00 -1.788D+00 9.D-01 9.D-01 5.D-01 7.D-01    0   0   0
  1 1.D+01 -1.969D+02 1.D+00 -5.660D+00 3.D-01 3.D-01 1.D+00 2.D-01   10C  0   0
  2 6.D+01 -1.630D+02 1.D+00 -4.684D+00 3.D-01 3.D-01 1.D-06 2.D-02   37C  0   0
  3 6.D+02 -1.598D+02 1.D+00 -4.591D+00 3.D-01 3.D-01 1.D-06 3.D-05   52C  0   0
  4 6.D+03 -1.598D+02 1.D+00 -4.592D+00 3.D-01 3.D-01 1.D-04 1.D-08   54C  0   0
  5 6.D+04 -1.598D+02 1.D+00 -4.592D+00 3.D-01 3.D-01 2.D-05 2.D-09   55C  0   0
  6 6.D+05 -1.598D+02 1.D+00 -4.592D+00 3.D-01 3.D-01 3.D-05 9.D-11   56C  0   0
  7 6.D+06 -1.598D+02 1.D+00 -4.592D+00 3.D-01 3.D-01 4.D-05 7.D-12   57C  0   0
  8 6.D+07 -1.598D+02 1.D+00 -4.592D+00 3.D-01 3.D-01 1.D-05 6.D-13   58C  0   0
  9 6.D+08 -1.598D+02 1.D+00 -4.592D+00 3.D-01 3.D-01 3.D-05 6.D-14   59C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 6.D+09 -1.598D+02 1.D+00 -4.592D+00 3.D-01 3.D-01 5.D-05 1.D-14   60C  0   0
 11 6.D+10 -1.598D+02 1.D+00 -4.592D+00 3.D-01 3.D-01 3.D-05 1.D-15   61C  0   0
 12 6.D+11 -1.598D+02 1.D+00 -4.592D+00 3.D-01 3.D-01 1.D-04 2.D-16   73C  0   0
 13 6.D+12 -1.598D+02 1.D+00 -4.592D+00 3.D-01 3.D-01 4.D-03 4.D-16   77P  0   0
 14 6.D+13 -1.598D+02 1.D+00 -4.592D+00 3.D-01 3.D-01 3.D-02 5.D-16   82P  0   0
 15 6.D+14 -1.598D+02 1.D+00 -4.592D+00 3.D-01 3.D-01 4.D+05 2.D-09   90P  0   0
 16 6.D+15 -1.598D+02 1.D+00 -4.592D+00 3.D-01 3.D-01 9.D+06 6.D-09  101P  0   0
 17 6.D+16 -1.598D+02 1.D+00 -4.592D+00 3.D-01 3.D-01 3.D+07 1.D-09  135P  0   0
 18 6.D+17 -1.598D+02 1.D+00 -4.592D+00 3.D-01 3.D-01 2.D+08 1.D-09  149P  0   0
 19 6.D+18 -1.598D+02 1.D+00 -4.592D+00 3.D-01 3.D-01 6.D+09 3.D-09  153P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 6.D+19 -1.598D+02 1.D+00 -4.592D+00 3.D-01 3.D-01 9.D+10 5.D-09  166P  0   0
 21 6.D+20 -1.598D+02 1.D+00 -4.592D+00 3.D-01 3.D-01 7.D+11 5.D-09  222P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.06

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   1007
 Subroutine evalg    (coded=T):    304
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  20741 (  1037 calls per constraint in average)
 Subroutine evaljac  (coded=T):   3723 (   186 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    221
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 31
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 3.6D-02
 Smallest constraints scale factor : 1.0D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -1.199D+02 4.D+00 -4.302D+00 4.D+00 4.D+00 1.D+00 1.D+00    0   0   0
  1 4.D+00 -2.657D+02 1.D+00 -9.534D+00 1.D+00 1.D+00 2.D+00 4.D-01   10C  0   0
  2 9.D+01 -1.676D+02 1.D+00 -6.014D+00 1.D+00 1.D+00 4.D-05 2.D-02   55C  0   0
  3 9.D+02 -1.649D+02 1.D+00 -5.917D+00 1.D+00 1.D+00 2.D-06 5.D-05   70C  0   0
  4 9.D+03 -1.649D+02 1.D+00 -5.917D+00 1.D+00 1.D+00 4.D-07 4.D-08   72C  0   0
  5 9.D+04 -1.649D+02 1.D+00 -5.917D+00 1.D+00 1.D+00 5.D-09 5.D-12   74C  0   0
  6 9.D+05 -1.649D+02 1.D+00 -5.917D+00 1.D+00 1.D+00 4.D-06 5.D-12   74C  0   0
  7 9.D+06 -1.649D+02 1.D+00 -5.917D+00 1.D+00 1.D+00 5.D-05 5.D-12   74C  0   0
  8 9.D+07 -1.649D+02 1.D+00 -5.917D+00 1.D+00 1.D+00 2.D-05 5.D-13   75C  0   0
  9 9.D+08 -1.649D+02 1.D+00 -5.917D+00 1.D+00 1.D+00 2.D-05 5.D-14   76C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 9.D+09 -1.649D+02 1.D+00 -5.917D+00 1.D+00 1.D+00 3.D-05 3.D-15   77C  0   0
 11 9.D+10 -1.649D+02 1.D+00 -5.917D+00 1.D+00 1.D+00 1.D-04 1.D-15   80C  0   0
 12 9.D+11 -1.649D+02 1.D+00 -5.917D+00 1.D+00 1.D+00 5.D-03 5.D-15   86P  0   0
 13 9.D+12 -1.649D+02 1.D+00 -5.917D+00 1.D+00 1.D+00 4.D-02 3.D-16   91P  0   0
 14 9.D+13 -1.649D+02 1.D+00 -5.917D+00 1.D+00 1.D+00 2.D+06 2.D-08   95P  0   0
 15 9.D+14 -1.649D+02 1.D+00 -5.917D+00 1.D+00 1.D+00 1.D+05 4.D-10  165P  0   0
 16 9.D+15 -1.649D+02 1.D+00 -5.917D+00 1.D+00 1.D+00 8.D+07 1.D-08  169P  0   0
 17 9.D+16 -1.649D+02 1.D+00 -5.917D+00 1.D+00 1.D+00 4.D+06 2.D-10  218P  0   0
 18 9.D+17 -1.649D+02 1.D+00 -5.917D+00 1.D+00 1.D+00 2.D+09 3.D-09  222P  0   0
 19 9.D+18 -1.649D+02 1.D+00 -5.917D+00 1.D+00 1.D+00 3.D+08 1.D-10  270P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 9.D+19 -1.649D+02 1.D+00 -5.917D+00 1.D+00 1.D+00 1.D+11 4.D-09  274P  0   0
 21 9.D+20 -1.649D+02 1.D+00 -5.917D+00 1.D+00 1.D+00 5.D+10 8.D-13  363P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.12

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   1876
 Subroutine evalg    (coded=T):    455
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  38282 (  1914 calls per constraint in average)
 Subroutine evaljac  (coded=T):   5024 (   251 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    363
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 32
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 5.3D-02
 Smallest constraints scale factor : 1.5D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -4.365D+01 4.D+00 -2.330D+00 3.D+00 3.D+00 1.D+00 3.D+00    0   0   0
  1 3.D+00 -8.518D+02 4.D+00 -4.547D+01 2.D+00 2.D+00 1.D+00 1.D+00   10C  0   0
  2 7.D+01 -2.817D+02 1.D+00 -1.503D+01 1.D+00 1.D+00 2.D-07 2.D-02   72C  0   0
  3 7.D+02 -2.789D+02 1.D+00 -1.489D+01 1.D+00 1.D+00 2.D-08 2.D-04   84C  0   0
  4 7.D+03 -2.789D+02 1.D+00 -1.489D+01 1.D+00 1.D+00 1.D-07 4.D-07   87C  0   0
  5 7.D+04 -2.789D+02 1.D+00 -1.489D+01 1.D+00 1.D+00 3.D-07 7.D-11   89C  0   0
  6 7.D+05 -2.789D+02 1.D+00 -1.489D+01 1.D+00 1.D+00 5.D-05 7.D-11   89C  0   0
  7 7.D+06 -2.789D+02 1.D+00 -1.489D+01 1.D+00 1.D+00 1.D-05 8.D-12   90C  0   0
  8 7.D+07 -2.789D+02 1.D+00 -1.489D+01 1.D+00 1.D+00 2.D-05 5.D-13   91C  0   0
  9 7.D+08 -2.789D+02 1.D+00 -1.489D+01 1.D+00 1.D+00 3.D-05 4.D-14   92C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 7.D+09 -2.789D+02 1.D+00 -1.489D+01 1.D+00 1.D+00 2.D-05 6.D-15   93C  0   0
 11 7.D+10 -2.789D+02 1.D+00 -1.489D+01 1.D+00 1.D+00 1.D-04 1.D-15   97C  0   0
 12 7.D+11 -2.789D+02 1.D+00 -1.489D+01 1.D+00 1.D+00 9.D-04 1.D-15  103P  0   0
 13 7.D+12 -2.789D+02 1.D+00 -1.489D+01 1.D+00 1.D+00 9.D-03 1.D-15  106P  0   0
 14 7.D+13 -2.789D+02 1.D+00 -1.489D+01 1.D+00 1.D+00 8.D-02 1.D-15  109P  0   0
 15 7.D+14 -2.789D+02 1.D+00 -1.489D+01 1.D+00 1.D+00 9.D+04 4.D-10  115P  0   0
 16 7.D+15 -2.789D+02 1.D+00 -1.489D+01 1.D+00 1.D+00 7.D+03 4.D-11  121P  0   0
 17 7.D+16 -2.789D+02 1.D+00 -1.489D+01 1.D+00 1.D+00 1.D+09 2.D-08  126P  0   0
 18 7.D+17 -2.789D+02 1.D+00 -1.489D+01 1.D+00 1.D+00 4.D+09 4.D-09  143P  0   0
 19 7.D+18 -2.789D+02 1.D+00 -1.489D+01 1.D+00 1.D+00 8.D+09 3.D-09  170P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 7.D+19 -2.789D+02 1.D+00 -1.489D+01 1.D+00 1.D+00 2.D+11 2.D-09  175P  0   0
 21 7.D+20 -2.789D+02 1.D+00 -1.489D+01 1.D+00 1.D+00 1.D+10 7.D-11  208P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.05

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):    914
 Subroutine evalg    (coded=T):    315
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  19404 (   970 calls per constraint in average)
 Subroutine evaljac  (coded=T):   3878 (   193 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    206
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 33
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 2.5D-02
 Smallest constraints scale factor : 8.1D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -1.092D+02 3.D+00 -2.756D+00 2.D+00 2.D+00 7.D-01 8.D-01    0   0   0
  1 9.D+00 -2.477D+02 1.D+00 -6.252D+00 3.D-01 3.D-01 1.D+00 1.D-01   10C  0   0
  2 6.D+01 -1.962D+02 1.D+00 -4.951D+00 2.D-01 2.D-01 1.D-06 2.D-02   35C  0   0
  3 6.D+02 -1.943D+02 1.D+00 -4.905D+00 2.D-01 2.D-01 4.D-06 1.D-05   41C  0   0
  4 6.D+03 -1.943D+02 1.D+00 -4.905D+00 2.D-01 2.D-01 1.D-06 3.D-09   43C  0   0
  5 6.D+04 -1.943D+02 1.D+00 -4.905D+00 2.D-01 2.D-01 7.D-06 8.D-11   44C  0   0
  6 6.D+05 -1.943D+02 1.D+00 -4.905D+00 2.D-01 2.D-01 8.D-05 8.D-11   44C  0   0
  7 6.D+06 -1.943D+02 1.D+00 -4.905D+00 2.D-01 2.D-01 5.D-05 2.D-11   45C  0   0
  8 6.D+07 -1.943D+02 1.D+00 -4.905D+00 2.D-01 2.D-01 6.D-05 2.D-12   46C  0   0
  9 6.D+08 -1.943D+02 1.D+00 -4.905D+00 2.D-01 2.D-01 1.D-04 9.D-14   47C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 6.D+09 -1.943D+02 1.D+00 -4.905D+00 2.D-01 2.D-01 5.D-05 2.D-14   48C  0   0
 11 6.D+10 -1.943D+02 1.D+00 -4.905D+00 2.D-01 2.D-01 5.D-05 1.D-15   49C  0   0
 12 6.D+11 -1.943D+02 1.D+00 -4.905D+00 2.D-01 2.D-01 9.D-04 2.D-15   56P  0   0
 13 6.D+12 -1.943D+02 1.D+00 -4.905D+00 2.D-01 2.D-01 1.D+04 8.D-09   66P  0   0
 14 6.D+13 -1.943D+02 1.D+00 -4.905D+00 2.D-01 2.D-01 3.D+03 1.D-10  105P  0   0
 15 6.D+14 -1.943D+02 1.D+00 -4.905D+00 2.D-01 2.D-01 4.D+05 2.D-09  110P  0   0
 16 6.D+15 -1.943D+02 1.D+00 -4.905D+00 2.D-01 2.D-01 1.D+07 8.D-09  119P  0   0
 17 6.D+16 -1.943D+02 1.D+00 -4.905D+00 2.D-01 2.D-01 9.D+07 5.D-09  188P  0   0
 18 6.D+17 -1.943D+02 1.D+00 -4.905D+00 2.D-01 2.D-01 4.D+07 2.D-11  222P  0   0
 19 6.D+18 -1.943D+02 1.D+00 -4.905D+00 2.D-01 2.D-01 6.D+09 4.D-09  226P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 6.D+19 -1.943D+02 1.D+00 -4.905D+00 2.D-01 2.D-01 2.D+11 3.D-09  234P  0   0
 21 6.D+20 -1.943D+02 1.D+00 -4.905D+00 2.D-01 2.D-01 2.D+11 1.D-09  274P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.08

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   1395
 Subroutine evalg    (coded=T):    350
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  28385 (  1419 calls per constraint in average)
 Subroutine evaljac  (coded=T):   3905 (   195 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    272
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 34
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 3.3D-02
 Smallest constraints scale factor : 9.8D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -1.229D+02 4.D+00 -4.051D+00 4.D+00 4.D+00 8.D-01 3.D+00    0   0   0
  1 4.D+00 -4.257D+02 1.D+00 -1.403D+01 1.D+00 1.D+00 1.D+00 5.D-01   10C  0   0
  2 9.D+01 -2.023D+02 1.D+00 -6.667D+00 1.D+00 1.D+00 2.D-05 1.D-02   20C  0   0
  3 9.D+02 -2.000D+02 1.D+00 -6.591D+00 1.D+00 1.D+00 4.D-09 4.D-06   29C  0   0
  4 9.D+03 -2.000D+02 1.D+00 -6.591D+00 1.D+00 1.D+00 3.D-07 4.D-10   31C  0   0
  5 9.D+04 -2.000D+02 1.D+00 -6.591D+00 1.D+00 1.D+00 5.D-05 4.D-10   31C  0   0
  6 9.D+05 -2.000D+02 1.D+00 -6.591D+00 1.D+00 1.D+00 7.D-05 7.D-11   35C  0   0
  7 9.D+06 -2.000D+02 1.D+00 -6.591D+00 1.D+00 1.D+00 5.D-09 8.D-12   37C  0   0
  8 9.D+07 -2.000D+02 1.D+00 -6.591D+00 1.D+00 1.D+00 3.D-05 3.D-13   38C  0   0
  9 9.D+08 -2.000D+02 1.D+00 -6.591D+00 1.D+00 1.D+00 1.D-05 3.D-14   39C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 9.D+09 -2.000D+02 1.D+00 -6.591D+00 1.D+00 1.D+00 3.D-05 4.D-15   40C  0   0
 11 9.D+10 -2.000D+02 1.D+00 -6.591D+00 1.D+00 1.D+00 4.D-05 7.D-16   41C  0   0
 12 9.D+11 -2.000D+02 1.D+00 -6.591D+00 1.D+00 1.D+00 7.D-04 8.D-16   47P  0   0
 13 9.D+12 -2.000D+02 1.D+00 -6.591D+00 1.D+00 1.D+00 3.D+03 3.D-10   58P  0   0
 14 9.D+13 -2.000D+02 1.D+00 -6.591D+00 1.D+00 1.D+00 4.D+05 4.D-09   76P  0   0
 15 9.D+14 -2.000D+02 1.D+00 -6.591D+00 1.D+00 1.D+00 2.D+00 3.D-11  150P  0   0
 16 9.D+15 -2.000D+02 1.D+00 -6.591D+00 1.D+00 1.D+00 9.D+07 1.D-08  166P  0   0
 17 9.D+16 -2.000D+02 1.D+00 -6.591D+00 1.D+00 1.D+00 8.D+08 8.D-09  271P  0   0
 18 9.D+17 -2.000D+02 1.D+00 -6.591D+00 1.D+00 1.D+00 1.D+10 1.D-08  358P  0   0
 19 9.D+18 -2.000D+02 1.D+00 -6.591D+00 1.D+00 1.D+00 7.D+09 9.D-10  589P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 9.D+19 -2.000D+02 1.D+00 -6.591D+00 1.D+00 1.D+00 4.D+11 4.D-09  593P  0   0
 21 9.D+20 -2.000D+02 1.D+00 -6.591D+00 1.D+00 1.D+00 1.D+06 6.D-12  624P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.15

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   2950
 Subroutine evalg    (coded=T):    693
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  59416 (  2970 calls per constraint in average)
 Subroutine evaljac  (coded=T):   7067 (   353 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    622
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 35
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 2.9D-02
 Smallest constraints scale factor : 7.0D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -1.385D+02 3.D+00 -4.024D+00 1.D+00 1.D+00 9.D-01 7.D-01    0   0   0
  1 3.D+01 -1.393D+02 1.D+00 -4.047D+00 3.D-01 3.D-01 1.D+00 3.D-02   10C  0   0
  2 4.D+01 -1.415D+02 1.D+00 -4.111D+00 3.D-01 3.D-01 2.D-05 4.D-02   27C  0   0
  3 4.D+02 -1.357D+02 1.D+00 -3.942D+00 3.D-01 3.D-01 8.D-06 6.D-05   46C  0   0
  4 4.D+03 -1.357D+02 1.D+00 -3.943D+00 3.D-01 3.D-01 2.D-05 8.D-08   48C  0   0
  5 4.D+04 -1.357D+02 1.D+00 -3.943D+00 3.D-01 3.D-01 5.D-06 3.D-10   53C  0   0
  6 4.D+05 -1.357D+02 1.D+00 -3.943D+00 3.D-01 3.D-01 8.D-06 1.D-11   54C  0   0
  7 4.D+06 -1.357D+02 1.D+00 -3.943D+00 3.D-01 3.D-01 9.D-05 1.D-11   54C  0   0
  8 4.D+07 -1.357D+02 1.D+00 -3.943D+00 3.D-01 3.D-01 3.D-05 2.D-12   55C  0   0
  9 4.D+08 -1.357D+02 1.D+00 -3.943D+00 3.D-01 3.D-01 5.D-05 1.D-13   56C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 4.D+09 -1.357D+02 1.D+00 -3.943D+00 3.D-01 3.D-01 1.D-05 1.D-14   57C  0   0
 11 4.D+10 -1.357D+02 1.D+00 -3.943D+00 3.D-01 3.D-01 2.D-05 9.D-16   58C  0   0
 12 4.D+11 -1.357D+02 1.D+00 -3.943D+00 3.D-01 3.D-01 7.D-05 2.D-16   59C  0   0
 13 4.D+12 -1.357D+02 1.D+00 -3.943D+00 3.D-01 3.D-01 1.D+03 9.D-10   65P  0   0
 14 4.D+13 -1.357D+02 1.D+00 -3.943D+00 3.D-01 3.D-01 2.D-02 2.D-13 1065M  0   0
 15 4.D+14 -1.357D+02 1.D+00 -3.943D+00 3.D-01 3.D-01 2.D+05 2.D-09 1069P  0   0
 16 4.D+15 -1.357D+02 1.D+00 -3.943D+00 3.D-01 3.D-01 6.D+06 6.D-09 1088P  0   0
 17 4.D+16 -1.357D+02 1.D+00 -3.943D+00 3.D-01 3.D-01 9.D+06 6.D-10 1095P  0   0
 18 4.D+17 -1.357D+02 1.D+00 -3.943D+00 3.D-01 3.D-01 2.D+08 1.D-09 1099P  0   0
 19 4.D+18 -1.357D+02 1.D+00 -3.943D+00 3.D-01 3.D-01 4.D+07 4.D-11 1125P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 4.D+19 -1.357D+02 1.D+00 -3.943D+00 3.D-01 3.D-01 2.D+10 2.D-09 1135P  0   0
 21 4.D+20 -1.357D+02 1.D+00 -3.943D+00 3.D-01 3.D-01 3.D+09 3.D-11 1249P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.24

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   2379
 Subroutine evalg    (coded=T):   1355
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  48631 (  2431 calls per constraint in average)
 Subroutine evaljac  (coded=T):  15762 (   788 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):   1248
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 36
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 6.1D-02
 Smallest constraints scale factor : 1.6D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -2.140D+01 4.D+00 -1.312D+00 4.D+00 4.D+00 7.D-01 4.D+00    0   0   0
  1 1.D+00 -1.569D+03 5.D+00 -9.620D+01 5.D+00 5.D+00 1.D+00 7.D+00   10C  0   0
  2 3.D+01 -2.629D+02 1.D+00 -1.612D+01 1.D+00 1.D+00 5.D-07 8.D-02   28C  0   0
  3 3.D+01 -2.423D+02 1.D+00 -1.486D+01 1.D+00 1.D+00 8.D-06 7.D-03   34C  0   0
  4 3.D+02 -2.431D+02 1.D+00 -1.490D+01 1.D+00 1.D+00 1.D-08 2.D-04   38C  0   0
  5 3.D+03 -2.430D+02 1.D+00 -1.490D+01 1.D+00 1.D+00 1.D-07 2.D-06   41C  0   0
  6 3.D+04 -2.430D+02 1.D+00 -1.490D+01 1.D+00 1.D+00 3.D-08 2.D-09   43C  0   0
  7 3.D+05 -2.430D+02 1.D+00 -1.490D+01 1.D+00 1.D+00 9.D-06 4.D-11   44C  0   0
  8 3.D+06 -2.430D+02 1.D+00 -1.490D+01 1.D+00 1.D+00 1.D-06 2.D-12   45C  0   0
  9 3.D+07 -2.430D+02 1.D+00 -1.490D+01 1.D+00 1.D+00 9.D-05 2.D-12   45C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 3.D+08 -2.430D+02 1.D+00 -1.490D+01 1.D+00 1.D+00 4.D-05 4.D-13   46C  0   0
 11 3.D+09 -2.430D+02 1.D+00 -1.490D+01 1.D+00 1.D+00 1.D-06 3.D-14   47C  0   0
 12 3.D+10 -2.430D+02 1.D+00 -1.490D+01 1.D+00 1.D+00 3.D-05 1.D-15   48C  0   0
 13 3.D+11 -2.430D+02 1.D+00 -1.490D+01 1.D+00 1.D+00 8.D-05 3.D-16   49C  0   0
 14 3.D+12 -2.430D+02 1.D+00 -1.490D+01 1.D+00 1.D+00 5.D-04 2.D-16   54P  0   0
 15 3.D+13 -2.430D+02 1.D+00 -1.490D+01 1.D+00 1.D+00 5.D+03 6.D-10   61P  0   0
 16 3.D+14 -2.430D+02 1.D+00 -1.490D+01 1.D+00 1.D+00 3.D+06 1.D-08   65P  0   0
 17 3.D+15 -2.430D+02 1.D+00 -1.490D+01 1.D+00 1.D+00 7.D+05 8.D-10  146P  0   0
 18 3.D+16 -2.430D+02 1.D+00 -1.490D+01 1.D+00 1.D+00 1.D+08 4.D-09  151P  0   0
 19 3.D+17 -2.430D+02 1.D+00 -1.490D+01 1.D+00 1.D+00 4.D+07 2.D-09  563P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 3.D+18 -2.430D+02 1.D+00 -1.490D+01 1.D+00 1.D+00 1.D+07 6.D-11  578P  0   0
 21 3.D+19 -2.430D+02 1.D+00 -1.490D+01 1.D+00 1.D+00 6.D+10 2.D-09  583P  0   0
 22 3.D+20 -2.430D+02 1.D+00 -1.490D+01 1.D+00 1.D+00 3.D+11 3.D-09  604P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.16

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   3344
 Subroutine evalg    (coded=T):    679
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  67302 (  3365 calls per constraint in average)
 Subroutine evaljac  (coded=T):   8034 (   401 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    602
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 37
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 2.5D-02
 Smallest constraints scale factor : 7.4D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -1.517D+02 2.D+00 -3.771D+00 9.D-01 9.D-01 7.D-01 5.D-01    0   0   0
  1 4.D+01 -1.720D+02 1.D+00 -4.276D+00 2.D-01 2.D-01 2.D+00 6.D-02   10C  0   0
  2 4.D+01 -1.684D+02 1.D+00 -4.187D+00 2.D-01 2.D-01 2.D-06 2.D-02   15C  0   0
  3 4.D+02 -1.422D+02 1.D+00 -3.536D+00 2.D-01 2.D-01 4.D-07 7.D-03  104C  0   0
  4 4.D+03 -1.436D+02 1.D+00 -3.570D+00 2.D-01 2.D-01 1.D-08 2.D-06  155C  0   0
  5 4.D+04 -1.436D+02 1.D+00 -3.570D+00 2.D-01 2.D-01 4.D-06 9.D-11  157C  0   0
  6 4.D+05 -1.436D+02 1.D+00 -3.570D+00 2.D-01 2.D-01 2.D-06 9.D-12  158C  0   0
  7 4.D+06 -1.436D+02 1.D+00 -3.570D+00 2.D-01 2.D-01 4.D-05 9.D-12  158C  0   0
  8 4.D+07 -1.436D+02 1.D+00 -3.570D+00 2.D-01 2.D-01 2.D-05 8.D-13  159C  0   0
  9 4.D+08 -1.436D+02 1.D+00 -3.570D+00 2.D-01 2.D-01 2.D-05 3.D-14  160C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 4.D+09 -1.436D+02 1.D+00 -3.570D+00 2.D-01 2.D-01 2.D-05 4.D-15  161C  0   0
 11 4.D+10 -1.436D+02 1.D+00 -3.570D+00 2.D-01 2.D-01 3.D-05 5.D-16  162C  0   0
 12 4.D+11 -1.436D+02 1.D+00 -3.570D+00 2.D-01 2.D-01 5.D-04 7.D-16  169P  0   0
 13 4.D+12 -1.436D+02 1.D+00 -3.570D+00 2.D-01 2.D-01 2.D-03 3.D-16  174P  0   0
 14 4.D+13 -1.436D+02 1.D+00 -3.570D+00 2.D-01 2.D-01 2.D-02 2.D-16  183P  0   0
 15 4.D+14 -1.436D+02 1.D+00 -3.570D+00 2.D-01 2.D-01 2.D+05 6.D-10  203P  0   0
 16 4.D+15 -1.436D+02 1.D+00 -3.570D+00 2.D-01 2.D-01 6.D+04 3.D-10  263P  0   0
 17 4.D+16 -1.436D+02 1.D+00 -3.570D+00 2.D-01 2.D-01 2.D+06 2.D-10  267P  0   0
 18 4.D+17 -1.436D+02 1.D+00 -3.570D+00 2.D-01 2.D-01 7.D+07 7.D-10  271P  0   0
 19 4.D+18 -1.436D+02 1.D+00 -3.570D+00 2.D-01 2.D-01 6.D+07 8.D-11  295P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 4.D+19 -1.436D+02 1.D+00 -3.570D+00 2.D-01 2.D-01 7.D+09 7.D-10  299P  0   0
 21 4.D+20 -1.436D+02 1.D+00 -3.570D+00 2.D-01 2.D-01 6.D+09 8.D-11  322P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.08

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   1309
 Subroutine evalg    (coded=T):    440
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  27475 (  1373 calls per constraint in average)
 Subroutine evaljac  (coded=T):   4867 (   243 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    321
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 38
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 9.8D-02
 Smallest constraints scale factor : 2.9D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -1.257D+01 4.D+00 -1.226D+00 4.D+00 4.D+00 8.D-01 6.D+00    0   0   0
  1 5.D-01 -6.564D+03 2.D+01 -6.403D+02 2.D+01 2.D+01 1.D-01 4.D+01   10C  0   0
  2 1.D+01 -3.408D+02 1.D+00 -3.325D+01 1.D+00 1.D+00 2.D-08 3.D-01   26C  0   0
  3 1.D+01 -3.547D+02 1.D+00 -3.460D+01 1.D+00 1.D+00 3.D-07 3.D-01   43C  0   0
  4 1.D+02 -2.988D+02 1.D+00 -2.914D+01 1.D+00 1.D+00 3.D-08 2.D-02   61C  0   0
  5 1.D+03 -2.978D+02 1.D+00 -2.905D+01 1.D+00 1.D+00 3.D-06 1.D-04   67C  0   0
  6 1.D+04 -2.978D+02 1.D+00 -2.905D+01 1.D+00 1.D+00 4.D-07 5.D-07   70C  0   0
  7 1.D+05 -2.978D+02 1.D+00 -2.905D+01 1.D+00 1.D+00 9.D-06 2.D-10   72C  0   0
  8 1.D+06 -2.978D+02 1.D+00 -2.905D+01 1.D+00 1.D+00 5.D-06 9.D-12   73C  0   0
  9 1.D+07 -2.978D+02 1.D+00 -2.905D+01 1.D+00 1.D+00 9.D-05 9.D-12   73C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 1.D+08 -2.978D+02 1.D+00 -2.905D+01 1.D+00 1.D+00 2.D-05 5.D-13   74C  0   0
 11 1.D+09 -2.978D+02 1.D+00 -2.905D+01 1.D+00 1.D+00 2.D-05 3.D-14   75C  0   0
 12 1.D+10 -2.978D+02 1.D+00 -2.905D+01 1.D+00 1.D+00 3.D-05 3.D-15   76C  0   0
 13 1.D+11 -2.978D+02 1.D+00 -2.905D+01 1.D+00 1.D+00 3.D-05 2.D-16   78C  0   0
 14 1.D+12 -2.978D+02 1.D+00 -2.905D+01 1.D+00 1.D+00 5.D-05 5.D-17   80C  0   0
 15 1.D+13 -2.978D+02 1.D+00 -2.905D+01 1.D+00 1.D+00 1.D-02 1.D-15   83P  0   0
 16 1.D+14 -2.978D+02 1.D+00 -2.905D+01 1.D+00 1.D+00 2.D-01 1.D-15   90P  0   0
 17 1.D+15 -2.978D+02 1.D+00 -2.905D+01 1.D+00 1.D+00 1.D+07 1.D-08   96P  0   0
 18 1.D+16 -2.978D+02 1.D+00 -2.905D+01 1.D+00 1.D+00 9.D+07 9.D-09  104P  0   0
 19 1.D+17 -2.978D+02 1.D+00 -2.905D+01 1.D+00 1.D+00 1.D+09 1.D-08  117P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 1.D+18 -2.978D+02 1.D+00 -2.905D+01 1.D+00 1.D+00 9.D+09 9.D-09  133P  0   0
 21 1.D+19 -2.978D+02 1.D+00 -2.905D+01 1.D+00 1.D+00 9.D+10 8.D-09  146P  0   0
 22 1.D+20 -2.978D+02 1.D+00 -2.905D+01 1.D+00 1.D+00 1.D+12 9.D-09  162P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.04

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):    599
 Subroutine evalg    (coded=T):    248
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  12609 (   630 calls per constraint in average)
 Subroutine evaljac  (coded=T):   3200 (   160 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    161
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 39
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 5.5D-02
 Smallest constraints scale factor : 1.5D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -5.687D+01 4.D+00 -3.103D+00 4.D+00 4.D+00 9.D-01 2.D+00    0   0   0
  1 3.D+00 -7.845D+02 4.D+00 -4.281D+01 2.D+00 2.D+00 1.D+00 1.D+00   10C  0   0
  2 7.D+01 -2.473D+02 1.D+00 -1.349D+01 1.D+00 1.D+00 2.D-06 3.D-02   43C  0   0
  3 7.D+01 -2.437D+02 1.D+00 -1.330D+01 1.D+00 1.D+00 1.D-05 9.D-04   47C  0   0
  4 7.D+02 -2.436D+02 1.D+00 -1.329D+01 1.D+00 1.D+00 5.D-07 1.D-05   50C  0   0
  5 7.D+03 -2.436D+02 1.D+00 -1.329D+01 1.D+00 1.D+00 2.D-05 1.D-08   52C  0   0
  6 7.D+04 -2.436D+02 1.D+00 -1.329D+01 1.D+00 1.D+00 4.D-10 3.D-10   54C  0   0
  7 7.D+05 -2.436D+02 1.D+00 -1.329D+01 1.D+00 1.D+00 6.D-06 7.D-12   55C  0   0
  8 7.D+06 -2.436D+02 1.D+00 -1.329D+01 1.D+00 1.D+00 7.D-05 7.D-12   55C  0   0
  9 7.D+07 -2.436D+02 1.D+00 -1.329D+01 1.D+00 1.D+00 4.D-05 6.D-13   56C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 7.D+08 -2.436D+02 1.D+00 -1.329D+01 1.D+00 1.D+00 3.D-05 6.D-14   57C  0   0
 11 7.D+09 -2.436D+02 1.D+00 -1.329D+01 1.D+00 1.D+00 4.D-05 7.D-15   58C  0   0
 12 7.D+10 -2.436D+02 1.D+00 -1.329D+01 1.D+00 1.D+00 5.D-05 7.D-16   59C  0   0
 13 7.D+11 -2.436D+02 1.D+00 -1.329D+01 1.D+00 1.D+00 1.D-03 1.D-15   65P  0   0
 14 7.D+12 -2.436D+02 1.D+00 -1.329D+01 1.D+00 1.D+00 4.D-03 1.D-16   71P  0   0
 15 7.D+13 -2.436D+02 1.D+00 -1.329D+01 1.D+00 1.D+00 4.D-02 2.D-16   79P  0   0
 16 7.D+14 -2.436D+02 1.D+00 -1.329D+01 1.D+00 1.D+00 6.D-01 3.D-16   82P  0   0
 17 7.D+15 -2.436D+02 1.D+00 -1.329D+01 1.D+00 1.D+00 8.D+07 1.D-08   86P  0   0
 18 7.D+16 -2.436D+02 1.D+00 -1.329D+01 1.D+00 1.D+00 5.D+06 2.D-10  102P  0   0
 19 7.D+17 -2.436D+02 1.D+00 -1.329D+01 1.D+00 1.D+00 3.D+08 1.D-09  106P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 7.D+18 -2.436D+02 1.D+00 -1.329D+01 1.D+00 1.D+00 4.D+10 1.D-08  130P  0   0
 21 7.D+19 -2.436D+02 1.D+00 -1.329D+01 1.D+00 1.D+00 4.D+11 1.D-08  154P  0   0
 22 7.D+20 -2.436D+02 1.D+00 -1.329D+01 1.D+00 1.D+00 1.D+11 2.D-10  158P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.05

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):    667
 Subroutine evalg    (coded=T):    240
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  13893 (   694 calls per constraint in average)
 Subroutine evaljac  (coded=T):   2825 (   141 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    156
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 40
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 3.5D-02
 Smallest constraints scale factor : 1.2D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -6.487D+01 4.D+00 -2.275D+00 4.D+00 4.D+00 1.D+00 5.D+00    0   0   0
  1 8.D-01 -1.363D+03 5.D+00 -4.779D+01 5.D+00 5.D+00 1.D+00 5.D+00   10C  0   0
  2 2.D+01 -3.122D+02 1.D+00 -1.095D+01 1.D+00 1.D+00 7.D-08 6.D-02   46C  0   0
  3 2.D+01 -3.029D+02 1.D+00 -1.062D+01 1.D+00 1.D+00 3.D-07 6.D-02   55C  0   0
  4 2.D+02 -2.979D+02 1.D+00 -1.045D+01 1.D+00 1.D+00 5.D-05 2.D-03   69C  0   0
  5 2.D+03 -2.978D+02 1.D+00 -1.044D+01 1.D+00 1.D+00 5.D-09 2.D-05   74C  0   0
  6 2.D+04 -2.978D+02 1.D+00 -1.044D+01 1.D+00 1.D+00 4.D-09 1.D-08   77C  0   0
  7 2.D+05 -2.978D+02 1.D+00 -1.044D+01 1.D+00 1.D+00 2.D-05 1.D-10   78C  0   0
  8 2.D+06 -2.978D+02 1.D+00 -1.044D+01 1.D+00 1.D+00 2.D-05 2.D-11   79C  0   0
  9 2.D+07 -2.978D+02 1.D+00 -1.044D+01 1.D+00 1.D+00 2.D-05 9.D-13   80C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 2.D+08 -2.978D+02 1.D+00 -1.044D+01 1.D+00 1.D+00 1.D-05 1.D-13   81C  0   0
 11 2.D+09 -2.978D+02 1.D+00 -1.044D+01 1.D+00 1.D+00 8.D-06 8.D-15   82C  0   0
 12 2.D+10 -2.978D+02 1.D+00 -1.044D+01 1.D+00 1.D+00 8.D-05 1.D-15   85C  0   0
 13 2.D+11 -2.978D+02 1.D+00 -1.044D+01 1.D+00 1.D+00 8.D-05 6.D-17   86C  0   0
 14 2.D+12 -2.978D+02 1.D+00 -1.044D+01 1.D+00 1.D+00 2.D-04 0.D+00   89P  0   0
 15 2.D+13 -2.978D+02 1.D+00 -1.044D+01 1.D+00 1.D+00 6.D+05 3.D-08   95P  0   0
 16 2.D+14 -2.978D+02 1.D+00 -1.044D+01 1.D+00 1.D+00 5.D+06 2.D-08  113P  0   0
 17 2.D+15 -2.978D+02 1.D+00 -1.044D+01 1.D+00 1.D+00 3.D+07 1.D-08  141P  0   0
 18 2.D+16 -2.978D+02 1.D+00 -1.044D+01 1.D+00 1.D+00 3.D+06 2.D-10  198P  0   0
 19 2.D+17 -2.978D+02 1.D+00 -1.044D+01 1.D+00 1.D+00 2.D+09 9.D-09  202P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 2.D+18 -2.978D+02 1.D+00 -1.044D+01 1.D+00 1.D+00 3.D+10 1.D-08  208P  0   0
 21 2.D+19 -2.978D+02 1.D+00 -1.044D+01 1.D+00 1.D+00 6.D+11 3.D-08  228P  0   0
 22 2.D+20 -2.978D+02 1.D+00 -1.044D+01 1.D+00 1.D+00 2.D+11 8.D-10  318P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.09

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   1496
 Subroutine evalg    (coded=T):    408
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  30634 (  1531 calls per constraint in average)
 Subroutine evaljac  (coded=T):   5077 (   253 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    316
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 41
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 3.4D-02
 Smallest constraints scale factor : 8.5D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -1.029D+02 4.D+00 -3.483D+00 4.D+00 4.D+00 9.D-01 1.D+00    0   0   0
  1 3.D+00 -5.425D+02 1.D+00 -1.836D+01 1.D+00 1.D+00 1.D+00 6.D-01   10C  0   0
  2 7.D+01 -2.745D+02 1.D+00 -9.287D+00 1.D+00 1.D+00 2.D-06 8.D-03   35C  0   0
  3 7.D+02 -2.722D+02 1.D+00 -9.210D+00 1.D+00 1.D+00 4.D-08 8.D-05   51C  0   0
  4 7.D+03 -2.722D+02 1.D+00 -9.210D+00 1.D+00 1.D+00 2.D-08 1.D-07   57C  0   0
  5 7.D+04 -2.722D+02 1.D+00 -9.210D+00 1.D+00 1.D+00 3.D-07 2.D-11   58C  0   0
  6 7.D+05 -2.722D+02 1.D+00 -9.210D+00 1.D+00 1.D+00 1.D-05 2.D-11   58C  0   0
  7 7.D+06 -2.722D+02 1.D+00 -9.210D+00 1.D+00 1.D+00 5.D-06 2.D-12   59C  0   0
  8 7.D+07 -2.722D+02 1.D+00 -9.210D+00 1.D+00 1.D+00 2.D-07 9.D-14   60C  0   0
  9 7.D+08 -2.722D+02 1.D+00 -9.210D+00 1.D+00 1.D+00 5.D-05 9.D-14   60C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 7.D+09 -2.722D+02 1.D+00 -9.210D+00 1.D+00 1.D+00 5.D-05 1.D-14   61C  0   0
 11 7.D+10 -2.722D+02 1.D+00 -9.210D+00 1.D+00 1.D+00 7.D-05 1.D-15   64C  0   0
 12 7.D+11 -2.722D+02 1.D+00 -9.210D+00 1.D+00 1.D+00 1.D-03 2.D-15   68P  0   0
 13 7.D+12 -2.722D+02 1.D+00 -9.210D+00 1.D+00 1.D+00 1.D-02 2.D-15   71P  0   0
 14 7.D+13 -2.722D+02 1.D+00 -9.210D+00 1.D+00 1.D+00 1.D-01 2.D-15   74P  0   0
 15 7.D+14 -2.722D+02 1.D+00 -9.210D+00 1.D+00 1.D+00 1.D+00 2.D-15   77P  0   0
 16 7.D+15 -2.722D+02 1.D+00 -9.210D+00 1.D+00 1.D+00 1.D+01 2.D-15   80P  0   0
 17 7.D+16 -2.722D+02 1.D+00 -9.210D+00 1.D+00 1.D+00 7.D+06 9.D-11  153P  0   0
 18 7.D+17 -2.722D+02 1.D+00 -9.210D+00 1.D+00 1.D+00 2.D+09 3.D-09  158P  0   0
 19 7.D+18 -2.722D+02 1.D+00 -9.210D+00 1.D+00 1.D+00 3.D+09 4.D-10  283P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 7.D+19 -2.722D+02 1.D+00 -9.210D+00 1.D+00 1.D+00 2.D+11 2.D-09  287P  0   0
 21 7.D+20 -2.722D+02 1.D+00 -9.210D+00 1.D+00 1.D+00 2.D+12 2.D-09  312P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.06

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   1441
 Subroutine evalg    (coded=T):    406
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  29581 (  1479 calls per constraint in average)
 Subroutine evaljac  (coded=T):   4679 (   233 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    312
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 42
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 3.1D-02
 Smallest constraints scale factor : 8.1D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -1.153D+02 3.D+00 -3.597D+00 1.D+00 1.D+00 8.D-01 1.D+00    0   0   0
  1 1.D+01 -2.482D+02 1.D+00 -7.747D+00 1.D+00 1.D+00 6.D-01 9.D-02   10C  0   0
  2 7.D+01 -2.341D+02 1.D+00 -7.306D+00 1.D+00 1.D+00 7.D-05 1.D-02   30C  0   0
  3 7.D+02 -2.281D+02 1.D+00 -7.117D+00 1.D+00 1.D+00 6.D-08 6.D-05   34C  0   0
  4 7.D+03 -2.281D+02 1.D+00 -7.117D+00 1.D+00 1.D+00 3.D-05 2.D-08   36C  0   0
  5 7.D+04 -2.281D+02 1.D+00 -7.117D+00 1.D+00 1.D+00 3.D-05 7.D-10   37C  0   0
  6 7.D+05 -2.281D+02 1.D+00 -7.117D+00 1.D+00 1.D+00 3.D-05 1.D-10   38C  0   0
  7 7.D+06 -2.281D+02 1.D+00 -7.117D+00 1.D+00 1.D+00 4.D-05 4.D-12   39C  0   0
  8 7.D+07 -2.281D+02 1.D+00 -7.117D+00 1.D+00 1.D+00 2.D-06 6.D-13   40C  0   0
  9 7.D+08 -2.281D+02 1.D+00 -7.117D+00 1.D+00 1.D+00 3.D-05 4.D-14   41C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 7.D+09 -2.281D+02 1.D+00 -7.117D+00 1.D+00 1.D+00 2.D-05 5.D-15   42C  0   0
 11 7.D+10 -2.281D+02 1.D+00 -7.117D+00 1.D+00 1.D+00 2.D-05 3.D-16   43C  0   0
 12 7.D+11 -2.281D+02 1.D+00 -7.117D+00 1.D+00 1.D+00 3.D-04 4.D-16   48P  0   0
 13 7.D+12 -2.281D+02 1.D+00 -7.117D+00 1.D+00 1.D+00 9.D+04 2.D-08   55P  0   0
 14 7.D+13 -2.281D+02 1.D+00 -7.117D+00 1.D+00 1.D+00 1.D+05 4.D-09  275P  0   0
 15 7.D+14 -2.281D+02 1.D+00 -7.117D+00 1.D+00 1.D+00 2.D+06 7.D-09  289P  0   0
 16 7.D+15 -2.281D+02 1.D+00 -7.117D+00 1.D+00 1.D+00 2.D+07 6.D-09  451P  0   0
 17 7.D+16 -2.281D+02 1.D+00 -7.117D+00 1.D+00 1.D+00 2.D+08 7.D-09  456P  0   0
 18 7.D+17 -2.281D+02 1.D+00 -7.117D+00 1.D+00 1.D+00 1.D+09 5.D-09  638P  0   0
 19 7.D+18 -2.281D+02 1.D+00 -7.117D+00 1.D+00 1.D+00 1.D+09 3.D-10  838P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 7.D+19 -2.281D+02 1.D+00 -7.117D+00 1.D+00 1.D+00 4.D+04 4.D-11 1082P  0   0
 21 7.D+20 -2.281D+02 1.D+00 -7.117D+00 1.D+00 1.D+00 7.D+12 3.D-08 1130P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.32

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   5655
 Subroutine evalg    (coded=T):   1208
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T): 113632 (  5681 calls per constraint in average)
 Subroutine evaljac  (coded=T):  12015 (   600 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):   1128
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 43
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 4.3D-02
 Smallest constraints scale factor : 1.4D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -4.769D+01 4.D+00 -2.063D+00 4.D+00 4.D+00 1.D+00 4.D+00    0   0   0
  1 1.D+00 -1.109D+03 3.D+00 -4.797D+01 3.D+00 3.D+00 9.D-01 3.D+00   10C  0   0
  2 3.D+01 -2.885D+02 1.D+00 -1.248D+01 1.D+00 1.D+00 1.D-05 4.D-02   52C  0   0
  3 3.D+01 -2.820D+02 1.D+00 -1.220D+01 1.D+00 1.D+00 3.D-09 5.D-02   73C  0   0
  4 3.D+02 -2.793D+02 1.D+00 -1.208D+01 1.D+00 1.D+00 6.D-09 5.D-03  130C  0   0
  5 3.D+03 -2.789D+02 1.D+00 -1.206D+01 1.D+00 1.D+00 2.D-05 1.D-05  143C  0   0
  6 3.D+04 -2.789D+02 1.D+00 -1.206D+01 1.D+00 1.D+00 3.D-09 4.D-09  146C  0   0
  7 3.D+05 -2.789D+02 1.D+00 -1.206D+01 1.D+00 1.D+00 7.D-10 1.D-13  148C  0   0
  8 3.D+06 -2.789D+02 1.D+00 -1.206D+01 1.D+00 1.D+00 4.D-07 1.D-13  148C  0   0
  9 3.D+07 -2.789D+02 1.D+00 -1.206D+01 1.D+00 1.D+00 5.D-06 1.D-13  148C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 3.D+08 -2.789D+02 1.D+00 -1.206D+01 1.D+00 1.D+00 5.D-05 1.D-13  148C  0   0
 11 3.D+09 -2.789D+02 1.D+00 -1.206D+01 1.D+00 1.D+00 5.D-05 2.D-14  149C  0   0
 12 3.D+10 -2.789D+02 1.D+00 -1.206D+01 1.D+00 1.D+00 4.D-05 9.D-16  150C  0   0
 13 3.D+11 -2.789D+02 1.D+00 -1.206D+01 1.D+00 1.D+00 9.D-05 4.D-16  151C  0   0
 14 3.D+12 -2.789D+02 1.D+00 -1.206D+01 1.D+00 1.D+00 2.D-03 2.D-16  154P  0   0
 15 3.D+13 -2.789D+02 1.D+00 -1.206D+01 1.D+00 1.D+00 3.D-02 1.D-16  158P  0   0
 16 3.D+14 -2.789D+02 1.D+00 -1.206D+01 1.D+00 1.D+00 3.D-01 1.D-16  162P  0   0
 17 3.D+15 -2.789D+02 1.D+00 -1.206D+01 1.D+00 1.D+00 4.D+07 4.D-08  166P  0   0
 18 3.D+16 -2.789D+02 1.D+00 -1.206D+01 1.D+00 1.D+00 3.D+08 2.D-08  171P  0   0
 19 3.D+17 -2.789D+02 1.D+00 -1.206D+01 1.D+00 1.D+00 2.D+09 2.D-08  188P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 3.D+18 -2.789D+02 1.D+00 -1.206D+01 1.D+00 1.D+00 2.D+10 2.D-08  195P  0   0
 21 3.D+19 -2.789D+02 1.D+00 -1.206D+01 1.D+00 1.D+00 3.D+08 7.D-13  224P  0   0
 22 3.D+20 -2.789D+02 1.D+00 -1.206D+01 1.D+00 1.D+00 6.D+12 6.D-08  228P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.05

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):    831
 Subroutine evalg    (coded=T):    346
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  17895 (   894 calls per constraint in average)
 Subroutine evaljac  (coded=T):   4227 (   211 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    227
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 44
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 1.8D-02
 Smallest constraints scale factor : 5.7D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -1.814D+02 4.D+00 -3.218D+00 4.D+00 4.D+00 8.D-01 3.D+00    0   0   0
  1 2.D+00 -3.818D+02 1.D+00 -6.775D+00 1.D+00 1.D+00 5.D-01 7.D-01   10C  0   0
  2 4.D+01 -2.529D+02 1.D+00 -4.488D+00 1.D+00 1.D+00 3.D-05 1.D-02   54C  0   0
  3 4.D+02 -2.437D+02 1.D+00 -4.325D+00 1.D+00 1.D+00 3.D-05 5.D-05   73C  0   0
  4 4.D+03 -2.438D+02 1.D+00 -4.326D+00 1.D+00 1.D+00 5.D-06 2.D-07   76C  0   0
  5 4.D+04 -2.438D+02 1.D+00 -4.326D+00 1.D+00 1.D+00 3.D-09 1.D-10   78C  0   0
  6 4.D+05 -2.438D+02 1.D+00 -4.326D+00 1.D+00 1.D+00 6.D-05 1.D-10   78C  0   0
  7 4.D+06 -2.438D+02 1.D+00 -4.326D+00 1.D+00 1.D+00 2.D-05 1.D-11   79C  0   0
  8 4.D+07 -2.438D+02 1.D+00 -4.326D+00 1.D+00 1.D+00 1.D-05 1.D-12   80C  0   0
  9 4.D+08 -2.438D+02 1.D+00 -4.326D+00 1.D+00 1.D+00 3.D-05 3.D-14   81C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 4.D+09 -2.438D+02 1.D+00 -4.326D+00 1.D+00 1.D+00 1.D-05 1.D-14   82C  0   0
 11 4.D+10 -2.438D+02 1.D+00 -4.326D+00 1.D+00 1.D+00 5.D-05 5.D-16   83C  0   0
 12 4.D+11 -2.438D+02 1.D+00 -4.326D+00 1.D+00 1.D+00 3.D+03 1.D-08   91P  0   0
 13 4.D+12 -2.438D+02 1.D+00 -4.326D+00 1.D+00 1.D+00 9.D+03 5.D-09  510P  0   0
 14 4.D+13 -2.438D+02 1.D+00 -4.326D+00 1.D+00 1.D+00 7.D+04 2.D-09  518P  0   0
 15 4.D+14 -2.438D+02 1.D+00 -4.326D+00 1.D+00 1.D+00 4.D+06 9.D-09  539P  0   0
 16 4.D+15 -2.438D+02 1.D+00 -4.326D+00 1.D+00 1.D+00 8.D+06 6.D-09  701P  0   0
 17 4.D+16 -2.438D+02 1.D+00 -4.326D+00 1.D+00 1.D+00 2.D+08 4.D-09  706P  0   0
 18 4.D+17 -2.438D+02 1.D+00 -4.326D+00 1.D+00 1.D+00 3.D+08 2.D-09  723P  0   0
 19 4.D+18 -2.438D+02 1.D+00 -4.326D+00 1.D+00 1.D+00 1.D+10 8.D-09  731P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 4.D+19 -2.438D+02 1.D+00 -4.326D+00 1.D+00 1.D+00 1.D+11 6.D-09  747P  0   0
 21 4.D+20 -2.438D+02 1.D+00 -4.326D+00 1.D+00 1.D+00 1.D+12 9.D-09  774P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.20

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   4031
 Subroutine evalg    (coded=T):    867
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  81438 (  4071 calls per constraint in average)
 Subroutine evaljac  (coded=T):   9002 (   450 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    772
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 45
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 4.4D-02
 Smallest constraints scale factor : 1.5D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -5.625D+01 4.D+00 -2.458D+00 4.D+00 4.D+00 1.D+00 3.D+00    0   0   0
  1 1.D+00 -9.990D+02 3.D+00 -4.365D+01 3.D+00 3.D+00 1.D+00 3.D+00   10C  0   0
  2 3.D+01 -2.490D+02 1.D+00 -1.088D+01 1.D+00 1.D+00 2.D-05 5.D-02   26C  0   0
  3 3.D+01 -2.376D+02 1.D+00 -1.038D+01 1.D+00 1.D+00 8.D-08 3.D-03   30C  0   0
  4 3.D+02 -2.379D+02 1.D+00 -1.040D+01 1.D+00 1.D+00 1.D-08 8.D-05   36C  0   0
  5 3.D+03 -2.379D+02 1.D+00 -1.040D+01 1.D+00 1.D+00 3.D-12 3.D-07   39C  0   0
  6 3.D+04 -2.379D+02 1.D+00 -1.040D+01 1.D+00 1.D+00 4.D-08 1.D-10   41C  0   0
  7 3.D+05 -2.379D+02 1.D+00 -1.040D+01 1.D+00 1.D+00 4.D-05 1.D-10   41C  0   0
  8 3.D+06 -2.379D+02 1.D+00 -1.040D+01 1.D+00 1.D+00 8.D-06 1.D-11   42C  0   0
  9 3.D+07 -2.379D+02 1.D+00 -1.040D+01 1.D+00 1.D+00 9.D-06 4.D-13   43C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 3.D+08 -2.379D+02 1.D+00 -1.040D+01 1.D+00 1.D+00 1.D-04 4.D-13   43C  0   0
 11 3.D+09 -2.379D+02 1.D+00 -1.040D+01 1.D+00 1.D+00 2.D-05 3.D-14   44C  0   0
 12 3.D+10 -2.379D+02 1.D+00 -1.040D+01 1.D+00 1.D+00 8.D-05 1.D-15   46C  0   0
 13 3.D+11 -2.379D+02 1.D+00 -1.040D+01 1.D+00 1.D+00 9.D+02 3.D-09   53P  0   0
 14 3.D+12 -2.379D+02 1.D+00 -1.040D+01 1.D+00 1.D+00 7.D+04 2.D-08   58P  0   0
 15 3.D+13 -2.379D+02 1.D+00 -1.040D+01 1.D+00 1.D+00 9.D+05 2.D-08   84P  0   0
 16 3.D+14 -2.379D+02 1.D+00 -1.040D+01 1.D+00 1.D+00 1.D+07 3.D-08  207P  0   0
 17 3.D+15 -2.379D+02 1.D+00 -1.040D+01 1.D+00 1.D+00 1.D+08 3.D-08  257P  0   0
 18 3.D+16 -2.379D+02 1.D+00 -1.040D+01 1.D+00 1.D+00 6.D+04 2.D-12  318P  0   0
 19 3.D+17 -2.379D+02 1.D+00 -1.040D+01 1.D+00 1.D+00 9.D+09 2.D-08  323P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 3.D+18 -2.379D+02 1.D+00 -1.040D+01 1.D+00 1.D+00 1.D+11 3.D-08  370P  0   0
 21 3.D+19 -2.379D+02 1.D+00 -1.040D+01 1.D+00 1.D+00 1.D+12 3.D-08  411P  0   0
 22 3.D+20 -2.379D+02 1.D+00 -1.040D+01 1.D+00 1.D+00 1.D+13 3.D-08  452P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.13

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   2259
 Subroutine evalg    (coded=T):    531
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  45662 (  2283 calls per constraint in average)
 Subroutine evaljac  (coded=T):   5624 (   281 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    456
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 46
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 4.2D-02
 Smallest constraints scale factor : 1.2D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -5.246D+01 4.D+00 -2.189D+00 4.D+00 4.D+00 9.D-01 5.D+00    0   0   0
  1 1.D+00 -1.124D+03 4.D+00 -4.687D+01 3.D+00 3.D+00 2.D+00 3.D+00   10C  0   0
  2 4.D+01 -3.075D+02 1.D+00 -1.283D+01 1.D+00 1.D+00 2.D-05 6.D-02   46C  0   0
  3 4.D+01 -3.014D+02 1.D+00 -1.257D+01 1.D+00 1.D+00 7.D-07 4.D-02   76C  0   0
  4 4.D+02 -2.978D+02 1.D+00 -1.242D+01 1.D+00 1.D+00 5.D-06 9.D-04  115C  0   0
  5 4.D+03 -2.978D+02 1.D+00 -1.242D+01 1.D+00 1.D+00 8.D-05 5.D-06  120C  0   0
  6 4.D+04 -2.978D+02 1.D+00 -1.242D+01 1.D+00 1.D+00 8.D-11 4.D-09  123C  0   0
  7 4.D+05 -2.978D+02 1.D+00 -1.242D+01 1.D+00 1.D+00 6.D-05 2.D-10  124C  0   0
  8 4.D+06 -2.978D+02 1.D+00 -1.242D+01 1.D+00 1.D+00 6.D-05 2.D-11  125C  0   0
  9 4.D+07 -2.978D+02 1.D+00 -1.242D+01 1.D+00 1.D+00 5.D-05 1.D-12  126C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 4.D+08 -2.978D+02 1.D+00 -1.242D+01 1.D+00 1.D+00 6.D-06 1.D-13  127C  0   0
 11 4.D+09 -2.978D+02 1.D+00 -1.242D+01 1.D+00 1.D+00 5.D-05 2.D-15  128C  0   0
 12 4.D+10 -2.978D+02 1.D+00 -1.242D+01 1.D+00 1.D+00 5.D-05 2.D-15  129C  0   0
 13 4.D+11 -2.978D+02 1.D+00 -1.242D+01 1.D+00 1.D+00 2.D+03 7.D-09  184P  0   0
 14 4.D+12 -2.978D+02 1.D+00 -1.242D+01 1.D+00 1.D+00 1.D+05 3.D-08  189P  0   0
 15 4.D+13 -2.978D+02 1.D+00 -1.242D+01 1.D+00 1.D+00 7.D+05 2.D-08  205P  0   0
 16 4.D+14 -2.978D+02 1.D+00 -1.242D+01 1.D+00 1.D+00 2.D+06 3.D-09  217P  0   0
 17 4.D+15 -2.978D+02 1.D+00 -1.242D+01 1.D+00 1.D+00 9.D+07 2.D-08  594P  0   0
 18 4.D+16 -2.978D+02 1.D+00 -1.242D+01 1.D+00 1.D+00 3.D+08 7.D-09  599P  0   0
 19 4.D+17 -2.978D+02 1.D+00 -1.242D+01 1.D+00 1.D+00 7.D+09 2.D-08  606P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 4.D+18 -2.978D+02 1.D+00 -1.242D+01 1.D+00 1.D+00 8.D+10 2.D-08  616P  0   0
 21 4.D+19 -2.978D+02 1.D+00 -1.242D+01 1.D+00 1.D+00 8.D+11 2.D-08  634P  0   0
 22 4.D+20 -2.978D+02 1.D+00 -1.242D+01 1.D+00 1.D+00 7.D+12 2.D-08  989P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.22

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   4790
 Subroutine evalg    (coded=T):   1104
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  97038 (  4851 calls per constraint in average)
 Subroutine evaljac  (coded=T):  13649 (   682 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    987
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 47
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 3.7D-02
 Smallest constraints scale factor : 1.0D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -1.003D+02 2.D+00 -3.667D+00 1.D+00 1.D+00 9.D-01 1.D+00    0   0   0
  1 1.D+01 -1.613D+02 1.D+00 -5.896D+00 3.D-01 3.D-01 1.D+00 2.D-01   10C  0   0
  2 6.D+01 -1.209D+02 3.D-01 -4.418D+00 4.D-02 4.D-02 1.D-05 2.D-02   63C  0   0
  3 6.D+01 -1.236D+02 3.D-01 -4.518D+00 5.D-02 5.D-02 6.D-05 4.D-03   73C  0   0
  4 6.D+02 -1.174D+02 4.D-03 -4.292D+00 1.D-03 5.D-03 1.D-09 1.D-03  116C  0   0
  5 6.D+02 -1.178D+02 3.D-03 -4.307D+00 4.D-04 4.D-04 3.D-06 8.D-05  122C  0   0
  6 6.D+02 -1.178D+02 6.D-06 -4.305D+00 6.D-06 3.D-05 6.D-05 6.D-06  124C  0   0

 NEWTON-KKT scheme in action!

 NEWTON-KKT Iteration                                           =           0
 Objective function value                                       = -1.1780D+02
 Maximal violation of selected nearly-active constraints        =  6.4495D-06
 Sup-norm of the gradient of the Lagrangian                     =  2.0303D-01

 Wrong Jacobian inertia. 
 Desired POS =      32 NEG =      22
 Actual  POS =      31 NEG =      23
 epsadd was increased to  1.0000D-07

 Wrong Jacobian inertia. 
 Desired POS =      32 NEG =      22
 Actual  POS =      31 NEG =      23
 epsadd was increased to  1.0000D-06

 Wrong Jacobian inertia. 
 Desired POS =      32 NEG =      22
 Actual  POS =      31 NEG =      23
 epsadd was increased to  1.0000D-05

 Wrong Jacobian inertia. 
 Desired POS =      32 NEG =      22
 Actual  POS =      31 NEG =      23
 epsadd was increased to  1.0000D-04

 Wrong Jacobian inertia. 
 Desired POS =      32 NEG =      22
 Actual  POS =      31 NEG =      23
 epsadd was increased to  1.0000D-03

 Wrong Jacobian inertia. 
 Desired POS =      32 NEG =      22
 Actual  POS =      31 NEG =      23
 epsadd was increased to  1.0000D-02

 Wrong Jacobian inertia. 
 Desired POS =      32 NEG =      22
 Actual  POS =      31 NEG =      23
 epsadd was increased to  1.0000D-01

 Wrong Jacobian inertia. 
 Desired POS =      32 NEG =      22
 Actual  POS =      31 NEG =      23
 epsadd was increased to  1.0000D+00

 Wrong Jacobian inertia. 
 Desired POS =      32 NEG =      22
 Actual  POS =      31 NEG =      23
 epsadd was increased to  1.0000D+01

 NEWTON-KKT Iteration                                           =           1
 Objective function value                                       = -1.1780D+02
 Maximal violation of selected nearly-active constraints        =  3.4146D-05
 Sup-norm of the gradient of the Lagrangian                     =  2.0303D-01

 NEWTON-KKT Iteration                                           =           2
 Objective function value                                       = -1.1780D+02
 Maximal violation of selected nearly-active constraints        =  5.1354D-05
 Sup-norm of the gradient of the Lagrangian                     =  1.0170D-01

 NEWTON-KKT Iteration                                           =           3
 Objective function value                                       = -1.1780D+02
 Maximal violation of selected nearly-active constraints        =  1.3119D-05
 Sup-norm of the gradient of the Lagrangian                     =  5.1029D-02

 NEWTON-KKT Iteration                                           =           4
 Objective function value                                       = -1.1780D+02
 Maximal violation of selected nearly-active constraints        =  3.2656D-06
 Sup-norm of the gradient of the Lagrangian                     =  2.5555D-02

 NEWTON-KKT Iteration                                           =           5
 Objective function value                                       = -1.1780D+02
 Maximal violation of selected nearly-active constraints        =  8.1897D-07
 Sup-norm of the gradient of the Lagrangian                     =  1.2798D-02

 NEWTON-KKT Iteration                                           =           6
 Objective function value                                       = -1.1780D+02
 Maximal violation of selected nearly-active constraints        =  2.0540D-07
 Sup-norm of the gradient of the Lagrangian                     =  6.4093D-03

 NEWTON-KKT Iteration                                           =           7
 Objective function value                                       = -1.1780D+02
 Maximal violation of selected nearly-active constraints        =  5.1514D-08
 Sup-norm of the gradient of the Lagrangian                     =  3.2098D-03

 NEWTON-KKT Iteration                                           =           8
 Objective function value                                       = -1.1780D+02
 Maximal violation of selected nearly-active constraints        =  2.1318D-08
 Sup-norm of the gradient of the Lagrangian                     =  2.0648D-03

 NEWTON-KKT Iteration                                           =           9
 Objective function value                                       = -1.1780D+02
 Maximal violation of selected nearly-active constraints        =  1.4988D-08
 Sup-norm of the gradient of the Lagrangian                     =  1.7314D-03

 NEWTON-KKT Iteration                                           =          10
 Objective function value                                       = -1.1780D+02
 Maximal violation of selected nearly-active constraints        =  1.0538D-08
 Sup-norm of the gradient of the Lagrangian                     =  1.4517D-03

 Flag of NEWTON-KKT = Maximum of iterations reached.
  7 6.D+02 -1.178D+02 2.D-05 -4.306D+00 2.D-06 2.D-06 3.D-07 5.D-07  126C  1  10

 NEWTON-KKT scheme in action!

 NEWTON-KKT Iteration                                           =           0
 Objective function value                                       = -1.1780D+02
 Maximal violation of selected nearly-active constraints        =  1.5853D-05
 Sup-norm of the gradient of the Lagrangian                     =  1.5824D-03

 NEWTON-KKT Iteration                                           =           1
 Objective function value                                       = -1.1780D+02
 Maximal violation of selected nearly-active constraints        =  1.5623D-04
 Sup-norm of the gradient of the Lagrangian                     =  1.1812D-08

 NEWTON-KKT Iteration                                           =           2
 Objective function value                                       = -1.1780D+02
 Maximal violation of selected nearly-active constraints        =  1.0418D-09
 Sup-norm of the gradient of the Lagrangian                     =  4.5646D-13

 Maximal violation of constraints                               =  4.3299D-15

 Maximal violation of Lagrange multipliers non-negativity       =  1.8148D-13

 GENCAN is being called to find the right multipliers.

 Maximal violation of Lagrange multipliers non-negativity       =  0.0000D+00
 Sup-norm of the gradient of the Lagrangian                     =  8.3379D-13

 Flag of NEWTON-KKT = KKT system solved!

 Flag of ALGENCAN: Solution was found.

 Total CPU time in seconds:     0.03

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):    318
 Subroutine evalg    (coded=T):    206
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):   7262 (   363 calls per constraint in average)
 Subroutine evaljac  (coded=T):   2655 (   132 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    134
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 48
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 5.6D-02
 Smallest constraints scale factor : 1.4D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -4.289D+01 4.D+00 -2.420D+00 4.D+00 4.D+00 1.D+00 2.D+00    0   0   0
  1 2.D+00 -8.937D+02 3.D+00 -5.042D+01 2.D+00 2.D+00 1.D+00 2.D+00   10C  0   0
  2 5.D+01 -2.601D+02 1.D+00 -1.467D+01 1.D+00 1.D+00 2.D-06 4.D-02   48C  0   0
  3 5.D+01 -2.492D+02 1.D+00 -1.406D+01 1.D+00 1.D+00 4.D-05 2.D-03   52C  0   0
  4 5.D+02 -2.494D+02 1.D+00 -1.407D+01 1.D+00 1.D+00 7.D-07 4.D-05   56C  0   0
  5 5.D+03 -2.494D+02 1.D+00 -1.407D+01 1.D+00 1.D+00 8.D-06 2.D-08   58C  0   0
  6 5.D+04 -2.494D+02 1.D+00 -1.407D+01 1.D+00 1.D+00 6.D-05 1.D-09   60C  0   0
  7 5.D+05 -2.494D+02 1.D+00 -1.407D+01 1.D+00 1.D+00 2.D-05 2.D-10   61C  0   0
  8 5.D+06 -2.494D+02 1.D+00 -1.407D+01 1.D+00 1.D+00 2.D-05 1.D-11   62C  0   0
  9 5.D+07 -2.494D+02 1.D+00 -1.407D+01 1.D+00 1.D+00 6.D-05 6.D-13   63C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 5.D+08 -2.494D+02 1.D+00 -1.407D+01 1.D+00 1.D+00 4.D-05 2.D-13   64C  0   0
 11 5.D+09 -2.494D+02 1.D+00 -1.407D+01 1.D+00 1.D+00 4.D-05 1.D-14   65C  0   0
 12 5.D+10 -2.494D+02 1.D+00 -1.407D+01 1.D+00 1.D+00 5.D-05 2.D-15   66C  0   0
 13 5.D+11 -2.494D+02 1.D+00 -1.407D+01 1.D+00 1.D+00 8.D-04 2.D-16   72P  0   0
 14 5.D+12 -1.786D+02 1.D+00 -1.008D+01 1.D+00 1.D+00 1.D+03 2.D-10  198P  0   0
 15 5.D+13 -1.786D+02 1.D+00 -1.008D+01 1.D+00 1.D+00 1.D+04 3.D-10  203P  0   0
 16 5.D+14 -1.786D+02 1.D+00 -1.008D+01 1.D+00 1.D+00 2.D+05 3.D-10  255P  0   0
 17 5.D+15 -1.786D+02 1.D+00 -1.008D+01 1.D+00 1.D+00 2.D+06 4.D-10  278P  0   0
 18 5.D+16 -1.786D+02 1.D+00 -1.008D+01 1.D+00 1.D+00 3.D+04 2.D-12  375P  0   0
 19 5.D+17 -1.786D+02 1.D+00 -1.008D+01 1.D+00 1.D+00 8.D+08 2.D-09  380P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 5.D+18 -1.786D+02 1.D+00 -1.008D+01 1.D+00 1.D+00 3.D+06 2.D-12  447P  0   0
 21 5.D+19 -1.786D+02 1.D+00 -1.008D+01 1.D+00 1.D+00 2.D+10 5.D-10  758P  0   0
 22 5.D+20 -1.786D+02 1.D+00 -1.008D+01 1.D+00 1.D+00 1.D+11 2.D-10  831P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.21

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   4040
 Subroutine evalg    (coded=T):    917
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  81443 (  4072 calls per constraint in average)
 Subroutine evaljac  (coded=T):   8210 (   410 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    828
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 49
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 2.3D-02
 Smallest constraints scale factor : 7.6D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -5.633D+01 4.D+00 -1.323D+00 4.D+00 4.D+00 4.D-01 3.D+00    0   0   0
  1 1.D+00 -9.225D+02 4.D+00 -2.166D+01 2.D+00 2.D+00 2.D+00 3.D+00   10C  0   0
  2 2.D+01 -3.065D+02 1.D+00 -7.197D+00 1.D+00 1.D+00 3.D-05 3.D-02   25C  0   0
  3 2.D+02 -2.977D+02 1.D+00 -6.992D+00 1.D+00 1.D+00 1.D-09 2.D-04   34C  0   0
  4 2.D+03 -2.978D+02 1.D+00 -6.992D+00 1.D+00 1.D+00 9.D-05 1.D-06   37C  0   0
  5 2.D+04 -2.978D+02 1.D+00 -6.992D+00 1.D+00 1.D+00 1.D-09 6.D-09   40C  0   0
  6 2.D+05 -2.978D+02 1.D+00 -6.992D+00 1.D+00 1.D+00 9.D-05 4.D-10   45C  0   0
  7 2.D+06 -2.978D+02 1.D+00 -6.992D+00 1.D+00 1.D+00 6.D-05 7.D-11   46C  0   0
  8 2.D+07 -2.978D+02 1.D+00 -6.992D+00 1.D+00 1.D+00 8.D-05 5.D-12   47C  0   0
  9 2.D+08 -2.978D+02 1.D+00 -6.992D+00 1.D+00 1.D+00 5.D-05 4.D-13   48C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 2.D+09 -2.978D+02 1.D+00 -6.992D+00 1.D+00 1.D+00 7.D-05 3.D-14   49C  0   0
 11 2.D+10 -2.978D+02 1.D+00 -6.992D+00 1.D+00 1.D+00 3.D-05 3.D-15   50C  0   0
 12 2.D+11 -2.978D+02 1.D+00 -6.992D+00 1.D+00 1.D+00 4.D-05 2.D-16   53C  0   0
 13 2.D+12 -2.978D+02 1.D+00 -6.992D+00 1.D+00 1.D+00 4.D-05 2.D-17   57C  0   0
 14 2.D+13 -2.978D+02 1.D+00 -6.992D+00 1.D+00 1.D+00 2.D-02 4.D-17   60P  0   0
 15 2.D+14 -2.978D+02 1.D+00 -6.992D+00 1.D+00 1.D+00 1.D-01 5.D-16   80P  0   0
 16 2.D+15 -2.978D+02 1.D+00 -6.992D+00 1.D+00 1.D+00 3.D+07 1.D-08   90P  0   0
 17 2.D+16 -2.978D+02 1.D+00 -6.992D+00 1.D+00 1.D+00 2.D+08 9.D-09   96P  0   0
 18 2.D+17 -2.978D+02 1.D+00 -6.992D+00 1.D+00 1.D+00 9.D+09 4.D-08  388P  0   0
 19 2.D+18 -2.978D+02 1.D+00 -6.992D+00 1.D+00 1.D+00 9.D+10 4.D-08  397P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 2.D+19 -2.978D+02 1.D+00 -6.992D+00 1.D+00 1.D+00 4.D+07 7.D-13  409P  0   0
 21 2.D+20 -2.978D+02 1.D+00 -6.992D+00 1.D+00 1.D+00 6.D+12 2.D-08  414P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.09

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   1828
 Subroutine evalg    (coded=T):    490
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  37031 (  1851 calls per constraint in average)
 Subroutine evaljac  (coded=T):   6009 (   300 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    413
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 50
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 5.9D-02
 Smallest constraints scale factor : 1.5D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -4.760D+01 3.D+00 -2.819D+00 2.D+00 2.D+00 1.D+00 2.D+00    0   0   0
  1 6.D+00 -5.100D+02 1.D+00 -3.020D+01 1.D+00 1.D+00 2.D+00 7.D-01   10C  0   0
  2 1.D+02 -2.535D+02 1.D+00 -1.501D+01 1.D+00 1.D+00 9.D-05 2.D-02   76C  0   0
  3 1.D+03 -2.494D+02 1.D+00 -1.477D+01 1.D+00 1.D+00 2.D-07 3.D-05   86C  0   0
  4 1.D+04 -2.494D+02 1.D+00 -1.477D+01 1.D+00 1.D+00 1.D-04 5.D-09   88C  0   0
  5 1.D+05 -2.494D+02 1.D+00 -1.477D+01 1.D+00 1.D+00 2.D-08 7.D-10   90C  0   0
  6 1.D+06 -2.494D+02 1.D+00 -1.477D+01 1.D+00 1.D+00 1.D-09 1.D-14   93C  0   0
  7 1.D+07 -2.494D+02 1.D+00 -1.477D+01 1.D+00 1.D+00 1.D-07 1.D-14   93C  0   0
  8 1.D+08 -2.494D+02 1.D+00 -1.477D+01 1.D+00 1.D+00 2.D-06 1.D-14   93C  0   0
  9 1.D+09 -2.494D+02 1.D+00 -1.477D+01 1.D+00 1.D+00 2.D-05 1.D-14   93C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 1.D+10 -2.494D+02 1.D+00 -1.477D+01 1.D+00 1.D+00 2.D-05 1.D-15   94C  0   0
 11 1.D+11 -2.494D+02 1.D+00 -1.477D+01 1.D+00 1.D+00 2.D+03 4.D-08  101P  0   0
 12 1.D+12 -2.494D+02 1.D+00 -1.477D+01 1.D+00 1.D+00 4.D+03 8.D-09  106P  0   0
 13 1.D+13 -2.494D+02 1.D+00 -1.477D+01 1.D+00 1.D+00 1.D+04 1.D-09  128P  0   0
 14 1.D+14 -2.494D+02 1.D+00 -1.477D+01 1.D+00 1.D+00 8.D+05 2.D-08  132P  0   0
 15 1.D+15 -2.494D+02 1.D+00 -1.477D+01 1.D+00 1.D+00 1.D+06 1.D-09  148P  0   0
 16 1.D+16 -2.494D+02 1.D+00 -1.477D+01 1.D+00 1.D+00 2.D+07 5.D-09  153P  0   0
 17 1.D+17 -2.494D+02 1.D+00 -1.477D+01 1.D+00 1.D+00 7.D+08 2.D-08  157P  0   0
 18 1.D+18 -2.494D+02 1.D+00 -1.477D+01 1.D+00 1.D+00 6.D+09 8.D-09  166P  0   0
 19 1.D+19 -2.494D+02 1.D+00 -1.477D+01 1.D+00 1.D+00 1.D+11 2.D-08  170P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 1.D+20 -2.494D+02 1.D+00 -1.477D+01 1.D+00 1.D+00 3.D+09 6.D-12  187P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.05

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):    884
 Subroutine evalg    (coded=T):    288
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  18726 (   936 calls per constraint in average)
 Subroutine evaljac  (coded=T):   3368 (   168 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    184
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 51
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 3.3D-02
 Smallest constraints scale factor : 8.9D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -9.554D+01 3.D+00 -3.197D+00 1.D+00 1.D+00 8.D-01 1.D+00    0   0   0
  1 1.D+01 -1.818D+02 1.D+00 -6.085D+00 4.D-01 4.D-01 7.D-01 2.D-01   10C  0   0
  2 6.D+01 -1.441D+02 1.D+00 -4.822D+00 4.D-01 4.D-01 9.D-06 1.D-02   48C  0   0
  3 6.D+02 -1.436D+02 1.D+00 -4.806D+00 4.D-01 4.D-01 8.D-06 2.D-05   62C  0   0
  4 6.D+03 -1.436D+02 1.D+00 -4.806D+00 4.D-01 4.D-01 8.D-05 7.D-09   80C  0   0
  5 6.D+04 -1.436D+02 1.D+00 -4.806D+00 4.D-01 4.D-01 7.D-06 1.D-09   82C  0   0
  6 6.D+05 -1.436D+02 1.D+00 -4.806D+00 4.D-01 4.D-01 1.D-04 2.D-11   85C  0   0
  7 6.D+06 -1.436D+02 1.D+00 -4.806D+00 4.D-01 4.D-01 1.D-05 2.D-11   89C  0   0
  8 6.D+07 -1.436D+02 1.D+00 -4.806D+00 4.D-01 4.D-01 1.D-07 2.D-13   91C  0   0
  9 6.D+08 -1.436D+02 1.D+00 -4.806D+00 4.D-01 4.D-01 5.D-05 2.D-13   91C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 6.D+09 -1.436D+02 1.D+00 -4.806D+00 4.D-01 4.D-01 1.D-05 2.D-15   92C  0   0
 11 6.D+10 -1.436D+02 1.D+00 -4.806D+00 4.D-01 4.D-01 6.D-05 4.D-16   95C  0   0
 12 6.D+11 -1.436D+02 1.D+00 -4.806D+00 4.D-01 4.D-01 9.D-05 2.D-16  172C  0   0
 13 6.D+12 -1.436D+02 1.D+00 -4.806D+00 4.D-01 4.D-01 9.D-05 0.D+00  320C  0   0
 14 6.D+13 -1.436D+02 1.D+00 -4.806D+00 4.D-01 4.D-01 9.D-05 0.D+00  320C  0   0
 15 6.D+14 -1.436D+02 1.D+00 -4.806D+00 4.D-01 4.D-01 9.D-05 0.D+00  320C  0   0
 16 6.D+15 -1.436D+02 1.D+00 -4.806D+00 4.D-01 4.D-01 9.D-05 0.D+00  320C  0   0
 17 6.D+16 -1.436D+02 1.D+00 -4.806D+00 4.D-01 4.D-01 9.D-05 0.D+00  320C  0   0
 18 6.D+17 -1.436D+02 1.D+00 -4.806D+00 4.D-01 4.D-01 9.D-05 0.D+00  320C  0   0
 19 6.D+18 -1.436D+02 1.D+00 -4.806D+00 4.D-01 4.D-01 9.D-05 0.D+00  320C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 6.D+19 -1.436D+02 1.D+00 -4.806D+00 4.D-01 4.D-01 9.D-05 0.D+00  320C  0   0
 21 6.D+20 -1.436D+02 1.D+00 -4.806D+00 4.D-01 4.D-01 9.D-05 0.D+00  320C  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.06

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):    684
 Subroutine evalg    (coded=T):    633
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  18907 (   945 calls per constraint in average)
 Subroutine evaljac  (coded=T):   8087 (   404 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    317
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 52
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 3.1D-02
 Smallest constraints scale factor : 8.0D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -1.338D+02 3.D+00 -4.095D+00 3.D+00 3.D+00 1.D+00 2.D+00    0   0   0
  1 6.D+00 -3.690D+02 1.D+00 -1.130D+01 1.D+00 1.D+00 7.D-01 2.D-01   10C  0   0
  2 8.D+01 -2.400D+02 1.D+00 -7.348D+00 1.D+00 1.D+00 2.D-05 9.D-03   41C  0   0
  3 8.D+02 -2.396D+02 1.D+00 -7.334D+00 1.D+00 1.D+00 6.D-06 2.D-05   53C  0   0
  4 8.D+03 -2.396D+02 1.D+00 -7.334D+00 1.D+00 1.D+00 3.D-05 8.D-09   55C  0   0
  5 8.D+04 -2.396D+02 1.D+00 -7.334D+00 1.D+00 1.D+00 2.D-05 4.D-10   56C  0   0
  6 8.D+05 -2.396D+02 1.D+00 -7.334D+00 1.D+00 1.D+00 2.D-05 4.D-11   57C  0   0
  7 8.D+06 -2.396D+02 1.D+00 -7.334D+00 1.D+00 1.D+00 1.D-05 2.D-12   58C  0   0
  8 8.D+07 -2.396D+02 1.D+00 -7.334D+00 1.D+00 1.D+00 3.D-06 3.D-13   59C  0   0
  9 8.D+08 -2.396D+02 1.D+00 -7.334D+00 1.D+00 1.D+00 3.D-06 5.D-15   60C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 8.D+09 -2.396D+02 1.D+00 -7.334D+00 1.D+00 1.D+00 5.D-05 5.D-15   60C  0   0
 11 8.D+10 -2.396D+02 1.D+00 -7.334D+00 1.D+00 1.D+00 8.D-05 5.D-16   61C  0   0
 12 8.D+11 -2.396D+02 1.D+00 -7.334D+00 1.D+00 1.D+00 1.D-03 1.D-15   66P  0   0
 13 8.D+12 -2.396D+02 1.D+00 -7.334D+00 1.D+00 1.D+00 1.D-02 1.D-15   70P  0   0
 14 8.D+13 -2.396D+02 1.D+00 -7.334D+00 1.D+00 1.D+00 1.D-01 1.D-15   73P  0   0
 15 8.D+14 -2.396D+02 1.D+00 -7.334D+00 1.D+00 1.D+00 4.D+06 5.D-09   77P  0   0
 16 8.D+15 -2.396D+02 1.D+00 -7.334D+00 1.D+00 1.D+00 7.D+07 2.D-08  158P  0   0
 17 8.D+16 -2.396D+02 1.D+00 -7.334D+00 1.D+00 1.D+00 3.D+07 2.D-09  264P  0   0
 18 8.D+17 -2.396D+02 1.D+00 -7.334D+00 1.D+00 1.D+00 2.D+09 7.D-09  268P  0   0
 19 8.D+18 -2.396D+02 1.D+00 -7.334D+00 1.D+00 1.D+00 3.D+07 3.D-12  412P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 8.D+19 -2.396D+02 1.D+00 -7.334D+00 1.D+00 1.D+00 1.D+11 6.D-09  416P  0   0
 21 8.D+20 -2.396D+02 1.D+00 -7.334D+00 1.D+00 1.D+00 5.D+12 2.D-08  424P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.15

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   2137
 Subroutine evalg    (coded=T):    505
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  43293 (  2164 calls per constraint in average)
 Subroutine evaljac  (coded=T):   6321 (   316 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    423
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 53
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 4.2D-02
 Smallest constraints scale factor : 1.2D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -6.950D+01 4.D+00 -2.910D+00 2.D+00 2.D+00 9.D-01 2.D+00    0   0   0
  1 5.D+00 -4.655D+02 1.D+00 -1.949D+01 1.D+00 1.D+00 1.D+00 5.D-01   10C  0   0
  2 1.D+02 -2.519D+02 1.D+00 -1.055D+01 1.D+00 1.D+00 4.D-06 2.D-02   76C  0   0
  3 1.D+03 -2.486D+02 1.D+00 -1.041D+01 1.D+00 1.D+00 7.D-08 4.D-05   89C  0   0
  4 1.D+04 -2.486D+02 1.D+00 -1.041D+01 1.D+00 1.D+00 4.D-07 3.D-08   92C  0   0
  5 1.D+05 -2.486D+02 1.D+00 -1.041D+01 1.D+00 1.D+00 9.D-05 1.D-09   94C  0   0
  6 1.D+06 -2.486D+02 1.D+00 -1.041D+01 1.D+00 1.D+00 3.D-05 9.D-11   95C  0   0
  7 1.D+07 -2.486D+02 1.D+00 -1.041D+01 1.D+00 1.D+00 7.D-05 6.D-12   96C  0   0
  8 1.D+08 -2.486D+02 1.D+00 -1.041D+01 1.D+00 1.D+00 2.D-05 9.D-13   97C  0   0
  9 1.D+09 -2.486D+02 1.D+00 -1.041D+01 1.D+00 1.D+00 5.D-05 6.D-14   98C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 1.D+10 -2.486D+02 1.D+00 -1.041D+01 1.D+00 1.D+00 3.D-05 6.D-15   99C  0   0
 11 1.D+11 -2.486D+02 1.D+00 -1.041D+01 1.D+00 1.D+00 1.D-04 6.D-16  101C  0   0
 12 1.D+12 -2.486D+02 1.D+00 -1.041D+01 1.D+00 1.D+00 5.D+03 2.D-08  109P  0   0
 13 1.D+13 -2.486D+02 1.D+00 -1.041D+01 1.D+00 1.D+00 3.D+04 3.D-09  144P  0   0
 14 1.D+14 -2.486D+02 1.D+00 -1.041D+01 1.D+00 1.D+00 1.D+04 4.D-10  186P  0   0
 15 1.D+15 -2.486D+02 1.D+00 -1.041D+01 1.D+00 1.D+00 3.D+06 3.D-09  214P  0   0
 16 1.D+16 -2.486D+02 1.D+00 -1.041D+01 1.D+00 1.D+00 7.D+06 7.D-10  288P  0   0
 17 1.D+17 -2.486D+02 1.D+00 -1.041D+01 1.D+00 1.D+00 1.D+08 1.D-09  310P  0   0
 18 1.D+18 -2.486D+02 1.D+00 -1.041D+01 1.D+00 1.D+00 2.D+09 2.D-09  339P  0   0
 19 1.D+19 -2.486D+02 1.D+00 -1.041D+01 1.D+00 1.D+00 2.D+10 2.D-09  353P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 1.D+20 -2.486D+02 1.D+00 -1.041D+01 1.D+00 1.D+00 1.D+09 1.D-12  369P  0   0
 21 1.D+21 -2.486D+02 1.D+00 -1.041D+01 1.D+00 1.D+00 1.D+12 1.D-09  386P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.10

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   1866
 Subroutine evalg    (coded=T):    494
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  38448 (  1922 calls per constraint in average)
 Subroutine evaljac  (coded=T):   5673 (   283 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    384
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 54
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 5.2D-02
 Smallest constraints scale factor : 1.2D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -4.954D+01 3.D+00 -2.566D+00 2.D+00 2.D+00 9.D-01 2.D+00    0   0   0
  1 6.D+00 -3.175D+02 1.D+00 -1.644D+01 7.D-01 7.D-01 1.D+00 5.D-01   10C  0   0
  2 2.D+02 -1.933D+02 1.D+00 -1.001D+01 7.D-01 7.D-01 7.D-06 8.D-03   60C  0   0
  3 2.D+03 -1.906D+02 1.D+00 -9.872D+00 7.D-01 7.D-01 6.D-06 9.D-06   74C  0   0
  4 2.D+04 -1.906D+02 1.D+00 -9.872D+00 7.D-01 7.D-01 7.D-07 1.D-09   76C  0   0
  5 2.D+05 -1.906D+02 1.D+00 -9.872D+00 7.D-01 7.D-01 2.D-05 1.D-10   77C  0   0
  6 2.D+06 -1.906D+02 1.D+00 -9.872D+00 7.D-01 7.D-01 4.D-06 1.D-11   78C  0   0
  7 2.D+07 -1.906D+02 1.D+00 -9.872D+00 7.D-01 7.D-01 7.D-06 5.D-13   79C  0   0
  8 2.D+08 -1.906D+02 1.D+00 -9.872D+00 7.D-01 7.D-01 8.D-05 5.D-13   79C  0   0
  9 2.D+09 -1.906D+02 1.D+00 -9.872D+00 7.D-01 7.D-01 5.D-05 4.D-14   80C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 2.D+10 -1.906D+02 1.D+00 -9.872D+00 7.D-01 7.D-01 8.D-05 4.D-15   81C  0   0
 11 2.D+11 -1.906D+02 1.D+00 -9.872D+00 7.D-01 7.D-01 1.D-04 5.D-16   85C  0   0
 12 2.D+12 -1.906D+02 1.D+00 -9.872D+00 7.D-01 7.D-01 6.D+02 1.D-09   94P  0   0
 13 2.D+13 -1.906D+02 1.D+00 -9.872D+00 7.D-01 7.D-01 2.D+05 1.D-08  101P  0   0
 14 2.D+14 -1.906D+02 1.D+00 -9.872D+00 7.D-01 7.D-01 2.D+05 1.D-09  375P  0   0
 15 2.D+15 -1.906D+02 1.D+00 -9.872D+00 7.D-01 7.D-01 2.D+06 4.D-09  386P  0   0
 16 2.D+16 -1.906D+02 1.D+00 -9.872D+00 7.D-01 7.D-01 9.D+07 5.D-09  395P  0   0
 17 2.D+17 -1.906D+02 1.D+00 -9.872D+00 7.D-01 7.D-01 5.D+08 1.D-08 1244P  0   0
 18 2.D+18 -1.906D+02 1.D+00 -9.872D+00 7.D-01 7.D-01 6.D+09 1.D-08 1279P  0   0
 19 2.D+19 -1.906D+02 1.D+00 -9.872D+00 7.D-01 7.D-01 7.D+08 4.D-11 1314P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 2.D+20 -1.906D+02 1.D+00 -9.872D+00 7.D-01 7.D-01 4.D+11 9.D-09 1318P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.41

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   7402
 Subroutine evalg    (coded=T):   1406
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T): 148801 (  7440 calls per constraint in average)
 Subroutine evaljac  (coded=T):  15405 (   770 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):   1317
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 55
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 4.0D-02
 Smallest constraints scale factor : 1.1D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -5.572D+01 3.D+00 -2.240D+00 3.D+00 3.D+00 7.D-01 3.D+00    0   0   0
  1 3.D+00 -5.293D+02 1.D+00 -2.128D+01 1.D+00 1.D+00 1.D+00 1.D+00   10C  0   0
  2 8.D+01 -2.540D+02 1.D+00 -1.021D+01 9.D-01 9.D-01 6.D-06 2.D-02   83C  0   0
  3 8.D+02 -2.494D+02 1.D+00 -1.002D+01 9.D-01 9.D-01 2.D-05 3.D-05  109C  0   0
  4 8.D+03 -2.494D+02 1.D+00 -1.002D+01 9.D-01 9.D-01 6.D-11 1.D-08  112C  0   0
  5 8.D+04 -2.494D+02 1.D+00 -1.002D+01 9.D-01 9.D-01 6.D-11 2.D-13  114C  0   0
  6 8.D+05 -2.494D+02 1.D+00 -1.002D+01 9.D-01 9.D-01 4.D-07 2.D-13  114C  0   0
  7 8.D+06 -2.494D+02 1.D+00 -1.002D+01 9.D-01 9.D-01 5.D-06 2.D-13  114C  0   0
  8 8.D+07 -2.494D+02 1.D+00 -1.002D+01 9.D-01 9.D-01 5.D-05 2.D-13  114C  0   0
  9 8.D+08 -2.494D+02 1.D+00 -1.002D+01 9.D-01 9.D-01 1.D-05 6.D-14  115C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 8.D+09 -2.494D+02 1.D+00 -1.002D+01 9.D-01 9.D-01 3.D-05 3.D-15  116C  0   0
 11 8.D+10 -2.494D+02 1.D+00 -1.002D+01 9.D-01 9.D-01 3.D-04 3.D-16  123P  0   0
 12 8.D+11 -2.494D+02 1.D+00 -1.002D+01 9.D-01 9.D-01 7.D+02 3.D-09  130P  0   0
 13 8.D+12 -2.494D+02 1.D+00 -1.002D+01 9.D-01 9.D-01 3.D+04 1.D-08  135P  0   0
 14 8.D+13 -2.494D+02 1.D+00 -1.002D+01 9.D-01 9.D-01 1.D+05 2.D-09  150P  0   0
 15 8.D+14 -2.494D+02 1.D+00 -1.002D+01 9.D-01 9.D-01 4.D+06 2.D-08  154P  0   0
 16 8.D+15 -2.494D+02 1.D+00 -1.002D+01 9.D-01 9.D-01 1.D+07 2.D-09  165P  0   0
 17 8.D+16 -2.494D+02 1.D+00 -1.002D+01 9.D-01 9.D-01 9.D+08 3.D-08  169P  0   0
 18 8.D+17 -2.494D+02 1.D+00 -1.002D+01 9.D-01 9.D-01 5.D+09 1.D-08  197P  0   0
 19 8.D+18 -2.494D+02 1.D+00 -1.002D+01 9.D-01 9.D-01 5.D+10 2.D-08  217P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 8.D+19 -2.494D+02 1.D+00 -1.002D+01 9.D-01 9.D-01 5.D+11 2.D-08  234P  0   0
 21 8.D+20 -2.494D+02 1.D+00 -1.002D+01 9.D-01 9.D-01 3.D+12 3.D-09  262P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.07

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   1176
 Subroutine evalg    (coded=T):    389
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  25036 (  1251 calls per constraint in average)
 Subroutine evaljac  (coded=T):   4414 (   220 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    259
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 56
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 3.6D-02
 Smallest constraints scale factor : 9.5D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -9.326D+01 3.D+00 -3.341D+00 1.D+00 1.D+00 8.D-01 1.D+00    0   0   0
  1 7.D+00 -3.997D+02 1.D+00 -1.432D+01 1.D+00 1.D+00 7.D-01 3.D-01   10C  0   0
  2 8.D+01 -2.395D+02 1.D+00 -8.582D+00 1.D+00 1.D+00 1.D-09 8.D-03   17C  0   0
  3 8.D+02 -2.379D+02 1.D+00 -8.524D+00 1.D+00 1.D+00 5.D-05 2.D-05   24C  0   0
  4 8.D+03 -2.379D+02 1.D+00 -8.524D+00 1.D+00 1.D+00 2.D-06 2.D-08   26C  0   0
  5 8.D+04 -2.379D+02 1.D+00 -8.524D+00 1.D+00 1.D+00 4.D-11 2.D-11   28C  0   0
  6 8.D+05 -2.379D+02 1.D+00 -8.524D+00 1.D+00 1.D+00 2.D-05 2.D-11   28C  0   0
  7 8.D+06 -2.379D+02 1.D+00 -8.524D+00 1.D+00 1.D+00 9.D-06 1.D-12   29C  0   0
  8 8.D+07 -2.379D+02 1.D+00 -8.524D+00 1.D+00 1.D+00 2.D-05 3.D-13   30C  0   0
  9 8.D+08 -2.379D+02 1.D+00 -8.524D+00 1.D+00 1.D+00 1.D-05 2.D-14   31C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 8.D+09 -2.379D+02 1.D+00 -8.524D+00 1.D+00 1.D+00 5.D-05 5.D-15   32C  0   0
 11 8.D+10 -2.379D+02 1.D+00 -8.524D+00 1.D+00 1.D+00 2.D-05 6.D-16   34C  0   0
 12 8.D+11 -2.379D+02 1.D+00 -8.524D+00 1.D+00 1.D+00 4.D-04 3.D-16   37P  0   0
 13 8.D+12 -2.379D+02 1.D+00 -8.524D+00 1.D+00 1.D+00 2.D-03 2.D-16   41P  0   0
 14 8.D+13 -2.379D+02 1.D+00 -8.524D+00 1.D+00 1.D+00 5.D-02 3.D-16   44P  0   0
 15 8.D+14 -2.379D+02 1.D+00 -8.524D+00 1.D+00 1.D+00 9.D+05 1.D-09  270P  0   0
 16 8.D+15 -2.379D+02 1.D+00 -8.524D+00 1.D+00 1.D+00 2.D+07 2.D-09  274P  0   0
 17 8.D+16 -2.379D+02 1.D+00 -8.524D+00 1.D+00 1.D+00 5.D+07 6.D-10  454P  0   0
 18 8.D+17 -2.379D+02 1.D+00 -8.524D+00 1.D+00 1.D+00 1.D+09 2.D-09  507P  0   0
 19 8.D+18 -2.379D+02 1.D+00 -8.524D+00 1.D+00 1.D+00 4.D+09 5.D-10  729P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 8.D+19 -2.379D+02 1.D+00 -8.524D+00 1.D+00 1.D+00 7.D+10 1.D-09  733P  0   0
 21 8.D+20 -2.379D+02 1.D+00 -8.524D+00 1.D+00 1.D+00 2.D+11 3.D-10  898P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.22

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   4541
 Subroutine evalg    (coded=T):    968
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  91153 (  4557 calls per constraint in average)
 Subroutine evaljac  (coded=T):   9509 (   475 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    901
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 57
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 2.4D-02
 Smallest constraints scale factor : 7.0D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -1.145D+02 4.D+00 -2.722D+00 4.D+00 4.D+00 8.D-01 1.D+00    0   0   0
  1 3.D+00 -5.243D+02 3.D+00 -1.247D+01 1.D+00 1.D+00 7.D-01 5.D-01   10C  0   0
  2 5.D+01 -2.665D+02 1.D+00 -6.337D+00 1.D+00 1.D+00 6.D-07 2.D-02   20C  0   0
  3 5.D+02 -2.622D+02 1.D+00 -6.235D+00 1.D+00 1.D+00 6.D-06 2.D-05   28C  0   0
  4 5.D+03 -2.622D+02 1.D+00 -6.235D+00 1.D+00 1.D+00 2.D-05 8.D-09   30C  0   0
  5 5.D+04 -2.622D+02 1.D+00 -6.235D+00 1.D+00 1.D+00 2.D-05 6.D-10   31C  0   0
  6 5.D+05 -2.622D+02 1.D+00 -6.235D+00 1.D+00 1.D+00 2.D-05 3.D-11   32C  0   0
  7 5.D+06 -2.622D+02 1.D+00 -6.235D+00 1.D+00 1.D+00 1.D-05 6.D-12   33C  0   0
  8 5.D+07 -2.622D+02 1.D+00 -6.235D+00 1.D+00 1.D+00 1.D-05 3.D-13   34C  0   0
  9 5.D+08 -2.622D+02 1.D+00 -6.235D+00 1.D+00 1.D+00 6.D-06 2.D-14   35C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 5.D+09 -2.622D+02 1.D+00 -6.235D+00 1.D+00 1.D+00 8.D-06 2.D-15   36C  0   0
 11 5.D+10 -2.622D+02 1.D+00 -6.235D+00 1.D+00 1.D+00 9.D-05 2.D-15   36C  0   0
 12 5.D+11 -2.622D+02 1.D+00 -6.235D+00 1.D+00 1.D+00 8.D-05 1.D-16   39C  0   0
 13 5.D+12 -2.622D+02 1.D+00 -6.235D+00 1.D+00 1.D+00 8.D-05 2.D-17   41C  0   0
 14 5.D+13 -2.622D+02 1.D+00 -6.235D+00 1.D+00 1.D+00 8.D-05 0.D+00   44C  0   0
 15 5.D+14 -2.622D+02 1.D+00 -6.235D+00 1.D+00 1.D+00 8.D-05 0.D+00   44C  0   0
 16 5.D+15 -2.622D+02 1.D+00 -6.235D+00 1.D+00 1.D+00 8.D-05 0.D+00   44C  0   0
 17 5.D+16 -2.622D+02 1.D+00 -6.235D+00 1.D+00 1.D+00 8.D-05 0.D+00   44C  0   0
 18 5.D+17 -2.622D+02 1.D+00 -6.235D+00 1.D+00 1.D+00 8.D-05 0.D+00   44C  0   0
 19 5.D+18 -2.622D+02 1.D+00 -6.235D+00 1.D+00 1.D+00 8.D-05 0.D+00   44C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 5.D+19 -2.622D+02 1.D+00 -6.235D+00 1.D+00 1.D+00 8.D-05 0.D+00   44C  0   0
 21 5.D+20 -2.622D+02 1.D+00 -6.235D+00 1.D+00 1.D+00 8.D-05 0.D+00   44C  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.01

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):    126
 Subroutine evalg    (coded=T):    117
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):   2911 (   145 calls per constraint in average)
 Subroutine evaljac  (coded=T):   1378 (    68 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):     47
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 58
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 2.7D-02
 Smallest constraints scale factor : 7.1D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -1.316D+02 4.D+00 -3.567D+00 4.D+00 4.D+00 9.D-01 2.D+00    0   0   0
  1 4.D+00 -4.616D+02 2.D+00 -1.251D+01 1.D+00 1.D+00 8.D-01 4.D-01   10C  0   0
  2 9.D+01 -2.442D+02 1.D+00 -6.618D+00 1.D+00 1.D+00 6.D-10 1.D-02   65C  0   0
  3 9.D+02 -2.436D+02 1.D+00 -6.602D+00 1.D+00 1.D+00 6.D-07 4.D-05   72C  0   0
  4 9.D+03 -2.436D+02 1.D+00 -6.602D+00 1.D+00 1.D+00 4.D-09 3.D-08   75C  0   0
  5 9.D+04 -2.436D+02 1.D+00 -6.602D+00 1.D+00 1.D+00 1.D-09 2.D-12   77C  0   0
  6 9.D+05 -2.436D+02 1.D+00 -6.602D+00 1.D+00 1.D+00 2.D-06 2.D-12   77C  0   0
  7 9.D+06 -2.436D+02 1.D+00 -6.602D+00 1.D+00 1.D+00 2.D-05 2.D-12   77C  0   0
  8 9.D+07 -2.436D+02 1.D+00 -6.602D+00 1.D+00 1.D+00 1.D-05 2.D-13   78C  0   0
  9 9.D+08 -2.436D+02 1.D+00 -6.602D+00 1.D+00 1.D+00 2.D-05 6.D-15   79C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 9.D+09 -2.436D+02 1.D+00 -6.602D+00 1.D+00 1.D+00 2.D-05 3.D-15   80C  0   0
 11 9.D+10 -2.436D+02 1.D+00 -6.602D+00 1.D+00 1.D+00 7.D-05 4.D-16   81C  0   0
 12 9.D+11 -2.436D+02 1.D+00 -6.602D+00 1.D+00 1.D+00 1.D-03 1.D-16   84P  0   0
 13 9.D+12 -2.436D+02 1.D+00 -6.602D+00 1.D+00 1.D+00 1.D-02 1.D-15   90P  0   0
 14 9.D+13 -2.436D+02 1.D+00 -6.602D+00 1.D+00 1.D+00 3.D+05 3.D-09  103P  0   0
 15 9.D+14 -2.436D+02 1.D+00 -6.602D+00 1.D+00 1.D+00 5.D+06 2.D-08  107P  0   0
 16 9.D+15 -1.836D+02 1.D+00 -4.976D+00 1.D+00 1.D+00 4.D+07 2.D-08  144P  0   0
 17 9.D+16 -1.836D+02 1.D+00 -4.976D+00 1.D+00 1.D+00 1.D+08 5.D-09  167P  0   0
 18 9.D+17 -1.836D+02 1.D+00 -4.976D+00 1.D+00 1.D+00 8.D+09 3.D-08  171P  0   0
 19 9.D+18 -1.836D+02 1.D+00 -4.976D+00 1.D+00 1.D+00 2.D+10 1.D-08  176P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 9.D+19 -1.836D+02 1.D+00 -4.976D+00 1.D+00 1.D+00 4.D+11 2.D-08  181P  0   0
 21 9.D+20 -1.836D+02 1.D+00 -4.976D+00 1.D+00 1.D+00 4.D+12 2.D-08  186P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.04

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):    779
 Subroutine evalg    (coded=T):    281
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  16439 (   821 calls per constraint in average)
 Subroutine evaljac  (coded=T):   3055 (   152 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    183
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 59
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 2.3D-02
 Smallest constraints scale factor : 7.1D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -2.218D+02 4.D+00 -5.120D+00 3.D+00 3.D+00 8.D-01 3.D+00    0   0   0
  1 6.D+00 -2.419D+02 1.D+00 -5.586D+00 1.D+00 1.D+00 1.D+00 1.D-01   10C  0   0
  2 5.D+01 -1.846D+02 1.D+00 -4.262D+00 1.D+00 1.D+00 5.D-05 3.D-02   41C  0   0
  3 5.D+02 -1.807D+02 1.D+00 -4.171D+00 1.D+00 1.D+00 1.D-11 2.D-05   52C  0   0
  4 5.D+03 -1.807D+02 1.D+00 -4.172D+00 1.D+00 1.D+00 3.D-05 3.D-08   58C  0   0
  5 5.D+04 -1.807D+02 1.D+00 -4.172D+00 1.D+00 1.D+00 2.D-09 5.D-10   59C  0   0
  6 5.D+05 -1.807D+02 1.D+00 -4.172D+00 1.D+00 1.D+00 1.D-04 2.D-10   61C  0   0
  7 5.D+06 -1.807D+02 1.D+00 -4.172D+00 1.D+00 1.D+00 5.D-05 6.D-12   62C  0   0
  8 5.D+07 -1.807D+02 1.D+00 -4.172D+00 1.D+00 1.D+00 6.D-05 1.D-12   63C  0   0
  9 5.D+08 -1.807D+02 1.D+00 -4.172D+00 1.D+00 1.D+00 2.D-05 1.D-13   64C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 5.D+09 -1.807D+02 1.D+00 -4.172D+00 1.D+00 1.D+00 1.D-05 4.D-15   65C  0   0
 11 5.D+10 -1.807D+02 1.D+00 -4.172D+00 1.D+00 1.D+00 5.D-05 9.D-16   66C  0   0
 12 5.D+11 -1.807D+02 1.D+00 -4.172D+00 1.D+00 1.D+00 2.D-03 3.D-15   74P  0   0
 13 5.D+12 -1.807D+02 1.D+00 -4.172D+00 1.D+00 1.D+00 4.D-03 7.D-16   79P  0   0
 14 5.D+13 -1.807D+02 1.D+00 -4.172D+00 1.D+00 1.D+00 1.D-02 2.D-16   84P  0   0
 15 5.D+14 -1.807D+02 1.D+00 -4.172D+00 1.D+00 1.D+00 3.D+03 6.D-12   87P  0   0
 16 5.D+15 -1.807D+02 1.D+00 -4.172D+00 1.D+00 1.D+00 2.D+06 3.D-10  160P  0   0
 17 5.D+16 -1.807D+02 1.D+00 -4.172D+00 1.D+00 1.D+00 1.D+09 2.D-08  164P  0   0
 18 5.D+17 -1.807D+02 1.D+00 -4.172D+00 1.D+00 1.D+00 1.D+10 3.D-08  184P  0   0
 19 5.D+18 -1.807D+02 1.D+00 -4.172D+00 1.D+00 1.D+00 1.D+11 3.D-08  226P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 5.D+19 -1.807D+02 1.D+00 -4.172D+00 1.D+00 1.D+00 1.D+10 2.D-10  302P  0   0
 21 5.D+20 -1.807D+02 1.D+00 -4.172D+00 1.D+00 1.D+00 7.D+12 1.D-08  306P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.10

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   1393
 Subroutine evalg    (coded=T):    392
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  28559 (  1427 calls per constraint in average)
 Subroutine evaljac  (coded=T):   4531 (   226 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    305
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 60
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 3.4D-02
 Smallest constraints scale factor : 8.8D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -1.106D+02 3.D+00 -3.767D+00 1.D+00 1.D+00 1.D+00 8.D-01    0   0   0
  1 1.D+01 -2.260D+02 1.D+00 -7.697D+00 4.D-01 4.D-01 1.D+00 1.D-01   10C  0   0
  2 8.D+01 -1.902D+02 1.D+00 -6.478D+00 4.D-01 4.D-01 4.D-05 2.D-02   80C  0   0
  3 8.D+02 -1.869D+02 1.D+00 -6.364D+00 4.D-01 4.D-01 1.D-09 2.D-05   88C  0   0
  4 8.D+03 -1.869D+02 1.D+00 -6.364D+00 4.D-01 4.D-01 1.D-05 4.D-09   90C  0   0
  5 8.D+04 -1.869D+02 1.D+00 -6.364D+00 4.D-01 4.D-01 3.D-05 5.D-10   91C  0   0
  6 8.D+05 -1.869D+02 1.D+00 -6.364D+00 4.D-01 4.D-01 2.D-05 5.D-11   92C  0   0
  7 8.D+06 -1.869D+02 1.D+00 -6.364D+00 4.D-01 4.D-01 1.D-05 3.D-12   93C  0   0
  8 8.D+07 -1.869D+02 1.D+00 -6.364D+00 4.D-01 4.D-01 5.D-06 4.D-13   94C  0   0
  9 8.D+08 -1.869D+02 1.D+00 -6.364D+00 4.D-01 4.D-01 2.D-05 3.D-14   95C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 8.D+09 -1.869D+02 1.D+00 -6.364D+00 4.D-01 4.D-01 3.D-05 5.D-15   96C  0   0
 11 8.D+10 -1.869D+02 1.D+00 -6.364D+00 4.D-01 4.D-01 4.D-05 4.D-16   99C  0   0
 12 8.D+11 -1.869D+02 1.D+00 -6.364D+00 4.D-01 4.D-01 6.D-04 2.D-16  107P  0   0
 13 8.D+12 -1.869D+02 1.D+00 -6.364D+00 4.D-01 4.D-01 6.D-03 4.D-16  110P  0   0
 14 8.D+13 -1.869D+02 1.D+00 -6.364D+00 4.D-01 4.D-01 4.D-02 5.D-16  113P  0   0
 15 8.D+14 -1.869D+02 1.D+00 -6.364D+00 4.D-01 4.D-01 4.D+06 5.D-09  117P  0   0
 16 8.D+15 -1.869D+02 1.D+00 -6.364D+00 4.D-01 4.D-01 5.D+04 3.D-11  142P  0   0
 17 8.D+16 -1.869D+02 1.D+00 -6.364D+00 4.D-01 4.D-01 1.D+08 5.D-09  146P  0   0
 18 8.D+17 -1.869D+02 1.D+00 -6.364D+00 4.D-01 4.D-01 7.D+06 9.D-12  151P  0   0
 19 8.D+18 -1.869D+02 1.D+00 -6.364D+00 4.D-01 4.D-01 3.D+10 1.D-08  155P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 8.D+19 -1.869D+02 1.D+00 -6.364D+00 4.D-01 4.D-01 5.D+08 3.D-11  306P  0   0
 21 8.D+20 -1.869D+02 1.D+00 -6.364D+00 4.D-01 4.D-01 5.D+11 2.D-09  310P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.09

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   1509
 Subroutine evalg    (coded=T):    410
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  31111 (  1555 calls per constraint in average)
 Subroutine evaljac  (coded=T):   4489 (   224 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    307
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 61
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 4.3D-02
 Smallest constraints scale factor : 1.4D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -5.593D+01 4.D+00 -2.404D+00 4.D+00 4.D+00 1.D+00 4.D+00    0   0   0
  1 1.D+00 -1.504D+03 4.D+00 -6.465D+01 4.D+00 4.D+00 6.D-01 4.D+00   10C  0   0
  2 3.D+01 -3.095D+02 1.D+00 -1.330D+01 1.D+00 1.D+00 4.D-05 5.D-02   38C  0   0
  3 3.D+01 -3.036D+02 1.D+00 -1.305D+01 1.D+00 1.D+00 2.D-07 6.D-02   63C  0   0
  4 3.D+02 -2.978D+02 1.D+00 -1.280D+01 1.D+00 1.D+00 3.D-06 2.D-03   84C  0   0
  5 3.D+03 -2.978D+02 1.D+00 -1.280D+01 1.D+00 1.D+00 3.D-05 1.D-05   89C  0   0
  6 3.D+04 -2.978D+02 1.D+00 -1.280D+01 1.D+00 1.D+00 2.D-09 9.D-09   92C  0   0
  7 3.D+05 -2.978D+02 1.D+00 -1.280D+01 1.D+00 1.D+00 7.D-05 3.D-10   93C  0   0
  8 3.D+06 -2.978D+02 1.D+00 -1.280D+01 1.D+00 1.D+00 2.D-05 2.D-11   94C  0   0
  9 3.D+07 -2.978D+02 1.D+00 -1.280D+01 1.D+00 1.D+00 5.D-06 4.D-13   95C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 3.D+08 -2.978D+02 1.D+00 -1.280D+01 1.D+00 1.D+00 7.D-06 3.D-14   96C  0   0
 11 3.D+09 -2.978D+02 1.D+00 -1.280D+01 1.D+00 1.D+00 9.D-05 3.D-14   96C  0   0
 12 3.D+10 -2.978D+02 1.D+00 -1.280D+01 1.D+00 1.D+00 6.D-06 3.D-15   99C  0   0
 13 3.D+11 -2.978D+02 1.D+00 -1.280D+01 1.D+00 1.D+00 2.D-05 8.D-17  101C  0   0
 14 3.D+12 -2.978D+02 1.D+00 -1.280D+01 1.D+00 1.D+00 2.D-03 0.D+00  104P  0   0
 15 3.D+13 -2.978D+02 1.D+00 -1.280D+01 1.D+00 1.D+00 2.D-02 9.D-16  111P  0   0
 16 3.D+14 -2.978D+02 1.D+00 -1.280D+01 1.D+00 1.D+00 2.D-01 6.D-17  115P  0   0
 17 3.D+15 -2.978D+02 1.D+00 -1.280D+01 1.D+00 1.D+00 6.D+07 2.D-08  119P  0   0
 18 3.D+16 -2.978D+02 1.D+00 -1.280D+01 1.D+00 1.D+00 3.D+08 1.D-08  124P  0   0
 19 3.D+17 -2.978D+02 1.D+00 -1.280D+01 1.D+00 1.D+00 3.D+09 9.D-09  133P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 3.D+18 -2.978D+02 1.D+00 -1.280D+01 1.D+00 1.D+00 3.D+10 9.D-09  140P  0   0
 21 3.D+19 -2.978D+02 1.D+00 -1.280D+01 1.D+00 1.D+00 3.D+10 1.D-09  145P  0   0
 22 3.D+20 -2.978D+02 1.D+00 -1.280D+01 1.D+00 1.D+00 2.D+12 8.D-09  152P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.04

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):    550
 Subroutine evalg    (coded=T):    249
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  11825 (   591 calls per constraint in average)
 Subroutine evaljac  (coded=T):   3178 (   158 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    152
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 62
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 5.5D-02
 Smallest constraints scale factor : 1.7D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -3.308D+01 4.D+00 -1.823D+00 4.D+00 4.D+00 9.D-01 3.D+00    0   0   0
  1 1.D+00 -1.362D+03 4.D+00 -7.506D+01 4.D+00 4.D+00 2.D+00 4.D+00   10C  0   0
  2 4.D+01 -3.123D+02 1.D+00 -1.721D+01 1.D+00 1.D+00 1.D-06 6.D-02   28C  0   0
  3 4.D+01 -3.021D+02 1.D+00 -1.665D+01 1.D+00 1.D+00 1.D-09 5.D-02   37C  0   0
  4 4.D+02 -2.978D+02 1.D+00 -1.641D+01 1.D+00 1.D+00 2.D-06 1.D-03   47C  0   0
  5 4.D+03 -2.978D+02 1.D+00 -1.640D+01 1.D+00 1.D+00 6.D-05 1.D-05   51C  0   0
  6 4.D+04 -2.978D+02 1.D+00 -1.640D+01 1.D+00 1.D+00 8.D-11 9.D-09   54C  0   0
  7 4.D+05 -2.978D+02 1.D+00 -1.640D+01 1.D+00 1.D+00 2.D-05 3.D-11   55C  0   0
  8 4.D+06 -2.978D+02 1.D+00 -1.640D+01 1.D+00 1.D+00 1.D-05 6.D-12   56C  0   0
  9 4.D+07 -2.978D+02 1.D+00 -1.640D+01 1.D+00 1.D+00 2.D-05 5.D-13   57C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 4.D+08 -2.978D+02 1.D+00 -1.640D+01 1.D+00 1.D+00 1.D-05 4.D-14   58C  0   0
 11 4.D+09 -2.978D+02 1.D+00 -1.640D+01 1.D+00 1.D+00 1.D-05 5.D-15   59C  0   0
 12 4.D+10 -2.978D+02 1.D+00 -1.640D+01 1.D+00 1.D+00 1.D-05 4.D-16   60C  0   0
 13 4.D+11 -2.978D+02 1.D+00 -1.640D+01 1.D+00 1.D+00 4.D-05 0.D+00   61C  0   0
 14 4.D+12 -2.978D+02 1.D+00 -1.640D+01 1.D+00 1.D+00 4.D-04 1.D-16   67P  0   0
 15 4.D+13 -2.978D+02 1.D+00 -1.640D+01 1.D+00 1.D+00 4.D-03 1.D-16   76P  0   0
 16 4.D+14 -2.978D+02 1.D+00 -1.640D+01 1.D+00 1.D+00 4.D+06 1.D-08   84P  0   0
 17 4.D+15 -2.978D+02 1.D+00 -1.640D+01 1.D+00 1.D+00 1.D+07 4.D-09  106P  0   0
 18 4.D+16 -2.978D+02 1.D+00 -1.640D+01 1.D+00 1.D+00 4.D+08 1.D-08  371P  0   0
 19 4.D+17 -2.978D+02 1.D+00 -1.640D+01 1.D+00 1.D+00 4.D+09 1.D-08  646P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 4.D+18 -2.978D+02 1.D+00 -1.640D+01 1.D+00 1.D+00 4.D+09 1.D-09  654P  0   0
 21 4.D+19 -2.978D+02 1.D+00 -1.640D+01 1.D+00 1.D+00 4.D+10 1.D-09  661P  0   0
 22 4.D+20 -2.978D+02 1.D+00 -1.640D+01 1.D+00 1.D+00 4.D+11 1.D-09  668P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.16

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   3524
 Subroutine evalg    (coded=T):    750
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  71045 (  3552 calls per constraint in average)
 Subroutine evaljac  (coded=T):   9421 (   471 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    666
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 63
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 3.6D-02
 Smallest constraints scale factor : 8.8D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -1.354D+02 4.D+00 -4.908D+00 3.D+00 3.D+00 1.D+00 4.D+00    0   0   0
  1 4.D+00 -4.305D+02 1.D+00 -1.560D+01 1.D+00 1.D+00 1.D+00 5.D-01   10C  0   0
  2 7.D+01 -2.320D+02 1.D+00 -8.409D+00 1.D+00 1.D+00 4.D-05 1.D-02   35C  0   0
  3 7.D+02 -2.293D+02 1.D+00 -8.313D+00 1.D+00 1.D+00 2.D-05 7.D-05   53C  0   0
  4 7.D+03 -2.293D+02 1.D+00 -8.313D+00 1.D+00 1.D+00 3.D-06 1.D-07   63C  0   0
  5 7.D+04 -2.293D+02 1.D+00 -8.313D+00 1.D+00 1.D+00 6.D-07 6.D-11   65C  0   0
  6 7.D+05 -2.293D+02 1.D+00 -8.313D+00 1.D+00 1.D+00 4.D-05 6.D-11   65C  0   0
  7 7.D+06 -2.293D+02 1.D+00 -8.313D+00 1.D+00 1.D+00 2.D-06 2.D-12   66C  0   0
  8 7.D+07 -2.293D+02 1.D+00 -8.313D+00 1.D+00 1.D+00 7.D-06 1.D-13   67C  0   0
  9 7.D+08 -2.293D+02 1.D+00 -8.313D+00 1.D+00 1.D+00 8.D-05 1.D-13   67C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 7.D+09 -2.293D+02 1.D+00 -8.313D+00 1.D+00 1.D+00 1.D-05 3.D-14   69C  0   0
 11 7.D+10 -2.293D+02 1.D+00 -8.313D+00 1.D+00 1.D+00 6.D-05 8.D-16   70C  0   0
 12 7.D+11 -2.293D+02 1.D+00 -8.313D+00 1.D+00 1.D+00 2.D-03 1.D-15   73P  0   0
 13 7.D+12 -2.293D+02 1.D+00 -8.313D+00 1.D+00 1.D+00 9.D-03 1.D-15   78P  0   0
 14 7.D+13 -2.293D+02 1.D+00 -8.313D+00 1.D+00 1.D+00 9.D-02 1.D-15   82P  0   0
 15 7.D+14 -2.293D+02 1.D+00 -8.313D+00 1.D+00 1.D+00 4.D+06 6.D-09   87P  0   0
 16 7.D+15 -2.293D+02 1.D+00 -8.313D+00 1.D+00 1.D+00 1.D+06 2.D-10  129P  0   0
 17 7.D+16 -2.293D+02 1.D+00 -8.313D+00 1.D+00 1.D+00 6.D+07 9.D-10  133P  0   0
 18 7.D+17 -2.293D+02 1.D+00 -8.313D+00 1.D+00 1.D+00 2.D+08 3.D-10  207P  0   0
 19 7.D+18 -2.293D+02 1.D+00 -8.313D+00 1.D+00 1.D+00 1.D+09 1.D-10  247P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 7.D+19 -2.293D+02 1.D+00 -8.313D+00 1.D+00 1.D+00 9.D+09 1.D-10  285P  0   0
 21 7.D+20 -2.293D+02 1.D+00 -8.313D+00 1.D+00 1.D+00 5.D+11 7.D-10  423P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.11

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   2017
 Subroutine evalg    (coded=T):    509
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  40968 (  2048 calls per constraint in average)
 Subroutine evaljac  (coded=T):   5373 (   268 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    423
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 64
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 3.1D-02
 Smallest constraints scale factor : 9.3D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -8.772D+01 3.D+00 -2.745D+00 3.D+00 3.D+00 8.D-01 2.D+00    0   0   0
  1 4.D+00 -4.594D+02 2.D+00 -1.438D+01 1.D+00 1.D+00 3.D+00 9.D-01   10C  0   0
  2 6.D+01 -2.534D+02 1.D+00 -7.930D+00 1.D+00 1.D+00 6.D-08 2.D-02   66C  0   0
  3 6.D+02 -2.494D+02 1.D+00 -7.805D+00 1.D+00 1.D+00 9.D-07 5.D-05   82C  0   0
  4 6.D+03 -2.494D+02 1.D+00 -7.805D+00 1.D+00 1.D+00 2.D-05 7.D-09   84C  0   0
  5 6.D+04 -2.494D+02 1.D+00 -7.805D+00 1.D+00 1.D+00 4.D-05 7.D-10   85C  0   0
  6 6.D+05 -2.494D+02 1.D+00 -7.805D+00 1.D+00 1.D+00 9.D-05 1.D-10   88C  0   0
  7 6.D+06 -2.494D+02 1.D+00 -7.805D+00 1.D+00 1.D+00 5.D-05 2.D-11   89C  0   0
  8 6.D+07 -2.494D+02 1.D+00 -7.805D+00 1.D+00 1.D+00 1.D-05 2.D-12   90C  0   0
  9 6.D+08 -2.494D+02 1.D+00 -7.805D+00 1.D+00 1.D+00 3.D-05 2.D-14   91C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 6.D+09 -2.494D+02 1.D+00 -7.805D+00 1.D+00 1.D+00 6.D-06 5.D-15   92C  0   0
 11 6.D+10 -2.494D+02 1.D+00 -7.805D+00 1.D+00 1.D+00 8.D-05 3.D-16   93C  0   0
 12 6.D+11 -2.494D+02 1.D+00 -7.805D+00 1.D+00 1.D+00 5.D+03 3.D-08  103P  0   0
 13 6.D+12 -2.494D+02 1.D+00 -7.805D+00 1.D+00 1.D+00 4.D+03 5.D-10  136P  0   0
 14 6.D+13 -2.494D+02 1.D+00 -7.805D+00 1.D+00 1.D+00 5.D+05 3.D-08  140P  0   0
 15 6.D+14 -2.494D+02 1.D+00 -7.805D+00 1.D+00 1.D+00 4.D+05 7.D-10  145P  0   0
 16 6.D+15 -2.494D+02 1.D+00 -7.805D+00 1.D+00 1.D+00 5.D+06 2.D-09  149P  0   0
 17 6.D+16 -2.494D+02 1.D+00 -7.805D+00 1.D+00 1.D+00 4.D+08 2.D-08  154P  0   0
 18 6.D+17 -2.494D+02 1.D+00 -7.805D+00 1.D+00 1.D+00 8.D+08 1.D-09  207P  0   0
 19 6.D+18 -2.494D+02 1.D+00 -7.805D+00 1.D+00 1.D+00 1.D+11 8.D-08  211P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 6.D+19 -2.494D+02 1.D+00 -7.805D+00 1.D+00 1.D+00 3.D+11 1.D-08  219P  0   0
 21 6.D+20 -2.494D+02 1.D+00 -7.805D+00 1.D+00 1.D+00 3.D+12 1.D-08  238P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.05

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   1146
 Subroutine evalg    (coded=T):    336
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  23844 (  1192 calls per constraint in average)
 Subroutine evaljac  (coded=T):   3732 (   186 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    235
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 65
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 4.4D-02
 Smallest constraints scale factor : 1.2D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -3.408D+01 4.D+00 -1.500D+00 2.D+00 2.D+00 7.D-01 2.D+00    0   0   0
  1 3.D+00 -6.629D+02 1.D+00 -2.918D+01 1.D+00 1.D+00 1.D+00 1.D+00   10C  0   0
  2 9.D+01 -2.660D+02 1.D+00 -1.171D+01 1.D+00 1.D+00 6.D-05 2.D-02   20C  0   0
  3 9.D+02 -2.622D+02 1.D+00 -1.154D+01 1.D+00 1.D+00 8.D-07 3.D-05   25C  0   0
  4 9.D+03 -2.622D+02 1.D+00 -1.154D+01 1.D+00 1.D+00 2.D-07 7.D-09   27C  0   0
  5 9.D+04 -2.622D+02 1.D+00 -1.154D+01 1.D+00 1.D+00 8.D-05 9.D-10   28C  0   0
  6 9.D+05 -2.622D+02 1.D+00 -1.154D+01 1.D+00 1.D+00 5.D-05 4.D-11   32C  0   0
  7 9.D+06 -2.622D+02 1.D+00 -1.154D+01 1.D+00 1.D+00 5.D-05 2.D-11   33C  0   0
  8 9.D+07 -2.622D+02 1.D+00 -1.154D+01 1.D+00 1.D+00 3.D-05 1.D-12   34C  0   0
  9 9.D+08 -2.622D+02 1.D+00 -1.154D+01 1.D+00 1.D+00 1.D-06 4.D-14   35C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 9.D+09 -2.622D+02 1.D+00 -1.154D+01 1.D+00 1.D+00 4.D-06 3.D-16   36C  0   0
 11 9.D+10 -2.622D+02 1.D+00 -1.154D+01 1.D+00 1.D+00 3.D-05 3.D-16   36C  0   0
 12 9.D+11 -2.622D+02 1.D+00 -1.154D+01 1.D+00 1.D+00 3.D-05 0.D+00   40C  0   0
 13 9.D+12 -2.622D+02 1.D+00 -1.154D+01 1.D+00 1.D+00 3.D-05 0.D+00   40C  0   0
 14 9.D+13 -2.622D+02 1.D+00 -1.154D+01 1.D+00 1.D+00 3.D-05 0.D+00   40C  0   0
 15 9.D+14 -2.622D+02 1.D+00 -1.154D+01 1.D+00 1.D+00 3.D-05 0.D+00   40C  0   0
 16 9.D+15 -2.622D+02 1.D+00 -1.154D+01 1.D+00 1.D+00 3.D-05 0.D+00   40C  0   0
 17 9.D+16 -2.622D+02 1.D+00 -1.154D+01 1.D+00 1.D+00 3.D-05 0.D+00   40C  0   0
 18 9.D+17 -2.622D+02 1.D+00 -1.154D+01 1.D+00 1.D+00 3.D-05 0.D+00   40C  0   0
 19 9.D+18 -2.622D+02 1.D+00 -1.154D+01 1.D+00 1.D+00 3.D-05 0.D+00   40C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 9.D+19 -2.622D+02 1.D+00 -1.154D+01 1.D+00 1.D+00 3.D-05 0.D+00   40C  0   0
 21 9.D+20 -2.622D+02 1.D+00 -1.154D+01 1.D+00 1.D+00 3.D-05 0.D+00   40C  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.02

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):    122
 Subroutine evalg    (coded=T):    110
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):   2794 (   139 calls per constraint in average)
 Subroutine evaljac  (coded=T):   1316 (    65 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):     42
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 66
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 3.2D-02
 Smallest constraints scale factor : 9.1D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -9.054D+01 4.D+00 -2.933D+00 4.D+00 4.D+00 8.D-01 3.D+00    0   0   0
  1 3.D+00 -6.300D+02 1.D+00 -2.041D+01 1.D+00 1.D+00 1.D+00 7.D-01   10C  0   0
  2 7.D+01 -2.800D+02 1.D+00 -9.072D+00 1.D+00 1.D+00 6.D-05 2.D-02   68C  0   0
  3 7.D+02 -2.789D+02 1.D+00 -9.036D+00 1.D+00 1.D+00 2.D-05 4.D-05   76C  0   0
  4 7.D+03 -2.789D+02 1.D+00 -9.036D+00 1.D+00 1.D+00 5.D-08 3.D-08   79C  0   0
  5 7.D+04 -2.789D+02 1.D+00 -9.036D+00 1.D+00 1.D+00 2.D-09 4.D-12   81C  0   0
  6 7.D+05 -2.789D+02 1.D+00 -9.036D+00 1.D+00 1.D+00 3.D-06 4.D-12   81C  0   0
  7 7.D+06 -2.789D+02 1.D+00 -9.036D+00 1.D+00 1.D+00 3.D-05 4.D-12   81C  0   0
  8 7.D+07 -2.789D+02 1.D+00 -9.036D+00 1.D+00 1.D+00 4.D-06 4.D-13   82C  0   0
  9 7.D+08 -2.789D+02 1.D+00 -9.036D+00 1.D+00 1.D+00 4.D-06 8.D-15   83C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 7.D+09 -2.789D+02 1.D+00 -9.036D+00 1.D+00 1.D+00 6.D-05 8.D-15   83C  0   0
 11 7.D+10 -2.789D+02 1.D+00 -9.036D+00 1.D+00 1.D+00 2.D-05 9.D-16   84C  0   0
 12 7.D+11 -2.789D+02 1.D+00 -9.036D+00 1.D+00 1.D+00 5.D-04 1.D-16   89P  0   0
 13 7.D+12 -2.789D+02 1.D+00 -9.036D+00 1.D+00 1.D+00 5.D-03 8.D-16   92P  0   0
 14 7.D+13 -2.789D+02 1.D+00 -9.036D+00 1.D+00 1.D+00 5.D-02 8.D-16   96P  0   0
 15 7.D+14 -2.789D+02 1.D+00 -9.036D+00 1.D+00 1.D+00 4.D-01 1.D-16   99P  0   0
 16 7.D+15 -2.789D+02 1.D+00 -9.036D+00 1.D+00 1.D+00 1.D+08 5.D-08  103P  0   0
 17 7.D+16 -2.789D+02 1.D+00 -9.036D+00 1.D+00 1.D+00 1.D+09 5.D-08  108P  0   0
 18 7.D+17 -2.789D+02 1.D+00 -9.036D+00 1.D+00 1.D+00 5.D+09 2.D-08  113P  0   0
 19 7.D+18 -2.789D+02 1.D+00 -9.036D+00 1.D+00 1.D+00 5.D+10 2.D-08  130P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 7.D+19 -2.789D+02 1.D+00 -9.036D+00 1.D+00 1.D+00 3.D+11 1.D-08  141P  0   0
 21 7.D+20 -2.789D+02 1.D+00 -9.036D+00 1.D+00 1.D+00 5.D+12 2.D-08  149P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.03

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):    586
 Subroutine evalg    (coded=T):    243
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  12562 (   628 calls per constraint in average)
 Subroutine evaljac  (coded=T):   2942 (   147 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    148
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 67
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 4.2D-02
 Smallest constraints scale factor : 1.1D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -7.258D+01 3.D+00 -3.026D+00 2.D+00 2.D+00 1.D+00 2.D+00    0   0   0
  1 5.D+00 -3.051D+02 1.D+00 -1.272D+01 1.D+00 1.D+00 3.D+00 6.D-01   10C  0   0
  2 1.D+02 -1.878D+02 1.D+00 -7.831D+00 1.D+00 1.D+00 3.D-07 2.D-02   34C  0   0
  3 1.D+03 -1.823D+02 1.D+00 -7.600D+00 1.D+00 1.D+00 1.D-06 2.D-05   43C  0   0
  4 1.D+04 -1.823D+02 1.D+00 -7.600D+00 1.D+00 1.D+00 1.D-05 4.D-09   45C  0   0
  5 1.D+05 -1.823D+02 1.D+00 -7.600D+00 1.D+00 1.D+00 4.D-05 4.D-10   46C  0   0
  6 1.D+06 -1.823D+02 1.D+00 -7.600D+00 1.D+00 1.D+00 3.D-05 8.D-11   47C  0   0
  7 1.D+07 -1.823D+02 1.D+00 -7.600D+00 1.D+00 1.D+00 3.D-05 6.D-12   48C  0   0
  8 1.D+08 -1.823D+02 1.D+00 -7.600D+00 1.D+00 1.D+00 3.D-05 2.D-13   49C  0   0
  9 1.D+09 -1.823D+02 1.D+00 -7.600D+00 1.D+00 1.D+00 3.D-05 3.D-14   50C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 1.D+10 -1.823D+02 1.D+00 -7.600D+00 1.D+00 1.D+00 1.D-05 6.D-15   51C  0   0
 11 1.D+11 -1.823D+02 1.D+00 -7.600D+00 1.D+00 1.D+00 8.D-05 9.D-16   54C  0   0
 12 1.D+12 -1.823D+02 1.D+00 -7.600D+00 1.D+00 1.D+00 3.D-04 3.D-16   60P  0   0
 13 1.D+13 -1.823D+02 1.D+00 -7.600D+00 1.D+00 1.D+00 3.D-03 2.D-16   65P  0   0
 14 1.D+14 -1.823D+02 1.D+00 -7.600D+00 1.D+00 1.D+00 1.D-02 2.D-16   71P  0   0
 15 1.D+15 -1.758D+02 1.D+00 -7.330D+00 8.D-01 8.D-01 8.D-01 1.D-01  109P  0   0
 16 1.D+16 -1.741D+02 1.D+00 -7.256D+00 8.D-01 8.D-01 2.D+01 1.D-03  121P  0   0
 17 1.D+17 -1.741D+02 1.D+00 -7.257D+00 8.D-01 8.D-01 6.D+01 1.D-05  129P  0   0
 18 1.D+18 -1.741D+02 1.D+00 -7.257D+00 8.D-01 8.D-01 9.D+02 9.D-08  137P  0   0
 19 1.D+19 -1.741D+02 1.D+00 -7.257D+00 8.D-01 8.D-01 1.D+04 8.D-10  147P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 1.D+20 -1.741D+02 1.D+00 -7.257D+00 8.D-01 8.D-01 1.D+05 7.D-12  161P  0   0
 21 1.D+21 -1.302D+02 1.D+00 -5.429D+00 8.D-01 8.D-01 1.D+05 1.D-02 1161M  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.20

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   3804
 Subroutine evalg    (coded=T):   2073
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  93357 (  4667 calls per constraint in average)
 Subroutine evaljac  (coded=T):  14064 (   703 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):   1156
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 68
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 4.0D-02
 Smallest constraints scale factor : 1.1D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -4.528D+01 4.D+00 -1.806D+00 4.D+00 4.D+00 6.D-01 3.D+00    0   0   0
  1 1.D+00 -1.124D+03 3.D+00 -4.484D+01 3.D+00 3.D+00 1.D+00 3.D+00   10C  0   0
  2 3.D+01 -2.874D+02 1.D+00 -1.146D+01 1.D+00 1.D+00 1.D-08 5.D-02   40C  0   0
  3 3.D+01 -2.814D+02 1.D+00 -1.122D+01 1.D+00 1.D+00 4.D-06 4.D-02   66C  0   0
  4 3.D+02 -2.792D+02 1.D+00 -1.114D+01 1.D+00 1.D+00 4.D-07 4.D-03  110C  0   0
  5 3.D+03 -2.789D+02 1.D+00 -1.112D+01 1.D+00 1.D+00 1.D-06 1.D-05  124C  0   0
  6 3.D+04 -2.789D+02 1.D+00 -1.112D+01 1.D+00 1.D+00 2.D-08 3.D-09  130C  0   0
  7 3.D+05 -2.789D+02 1.D+00 -1.112D+01 1.D+00 1.D+00 6.D-05 2.D-10  131C  0   0
  8 3.D+06 -2.789D+02 1.D+00 -1.112D+01 1.D+00 1.D+00 3.D-08 5.D-12  134C  0   0
  9 3.D+07 -2.789D+02 1.D+00 -1.112D+01 1.D+00 1.D+00 3.D-05 9.D-13  135C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 3.D+08 -2.789D+02 1.D+00 -1.112D+01 1.D+00 1.D+00 1.D-05 8.D-14  136C  0   0
 11 3.D+09 -2.789D+02 1.D+00 -1.112D+01 1.D+00 1.D+00 3.D-05 6.D-15  137C  0   0
 12 3.D+10 -2.789D+02 1.D+00 -1.112D+01 1.D+00 1.D+00 4.D-05 9.D-16  138C  0   0
 13 3.D+11 -2.789D+02 1.D+00 -1.112D+01 1.D+00 1.D+00 3.D-04 8.D-17  144P  0   0
 14 3.D+12 -2.789D+02 1.D+00 -1.112D+01 1.D+00 1.D+00 3.D-03 4.D-16  147P  0   0
 15 3.D+13 -2.789D+02 1.D+00 -1.112D+01 1.D+00 1.D+00 3.D+05 3.D-08  153P  0   0
 16 3.D+14 -2.789D+02 1.D+00 -1.112D+01 1.D+00 1.D+00 1.D+06 4.D-09  159P  0   0
 17 3.D+15 -2.789D+02 1.D+00 -1.112D+01 1.D+00 1.D+00 2.D+07 4.D-09  165P  0   0
 18 3.D+16 -2.789D+02 1.D+00 -1.112D+01 1.D+00 1.D+00 2.D+08 1.D-08  182P  0   0
 19 3.D+17 -2.789D+02 1.D+00 -1.112D+01 1.D+00 1.D+00 2.D+09 2.D-08  203P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 3.D+18 -2.789D+02 1.D+00 -1.112D+01 1.D+00 1.D+00 2.D+10 1.D-08  211P  0   0
 21 3.D+19 -2.789D+02 1.D+00 -1.112D+01 1.D+00 1.D+00 2.D+11 6.D-09  219P  0   0
 22 3.D+20 -2.789D+02 1.D+00 -1.112D+01 1.D+00 1.D+00 2.D+12 5.D-09  253P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.04

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   1061
 Subroutine evalg    (coded=T):    366
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  22368 (  1118 calls per constraint in average)
 Subroutine evaljac  (coded=T):   4399 (   219 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    251
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 69
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 2.8D-02
 Smallest constraints scale factor : 8.7D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -1.273D+02 4.D+00 -3.603D+00 2.D+00 2.D+00 1.D+00 1.D+00    0   0   0
  1 7.D+00 -1.958D+02 1.D+00 -5.542D+00 1.D+00 1.D+00 1.D-01 2.D-01   10C  0   0
  2 5.D+01 -1.666D+02 1.D+00 -4.715D+00 1.D+00 1.D+00 8.D-07 1.D-02   40C  0   0
  3 5.D+02 -1.627D+02 1.D+00 -4.605D+00 1.D+00 1.D+00 1.D-05 9.D-05   48C  0   0
  4 5.D+03 -1.627D+02 1.D+00 -4.606D+00 1.D+00 1.D+00 7.D-10 3.D-07   52C  0   0
  5 5.D+04 -1.627D+02 1.D+00 -4.606D+00 1.D+00 1.D+00 5.D-09 1.D-11   54C  0   0
  6 5.D+05 -1.627D+02 1.D+00 -4.606D+00 1.D+00 1.D+00 2.D-05 1.D-11   54C  0   0
  7 5.D+06 -1.627D+02 1.D+00 -4.606D+00 1.D+00 1.D+00 3.D-06 4.D-12   55C  0   0
  8 5.D+07 -1.627D+02 1.D+00 -4.606D+00 1.D+00 1.D+00 1.D-05 2.D-13   56C  0   0
  9 5.D+08 -1.627D+02 1.D+00 -4.606D+00 1.D+00 1.D+00 7.D-06 3.D-14   57C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 5.D+09 -1.627D+02 1.D+00 -4.606D+00 1.D+00 1.D+00 1.D-05 4.D-15   58C  0   0
 11 5.D+10 -1.627D+02 1.D+00 -4.606D+00 1.D+00 1.D+00 4.D-05 4.D-16   59C  0   0
 12 5.D+11 -1.627D+02 1.D+00 -4.606D+00 1.D+00 1.D+00 2.D-04 5.D-16   66P  0   0
 13 5.D+12 -1.627D+02 1.D+00 -4.606D+00 1.D+00 1.D+00 2.D-03 1.D-16   71P  0   0
 14 5.D+13 -1.627D+02 1.D+00 -4.606D+00 1.D+00 1.D+00 2.D-02 4.D-16   76P  0   0
 15 5.D+14 -1.627D+02 1.D+00 -4.606D+00 1.D+00 1.D+00 6.D+02 1.D-12  302P  0   0
 16 5.D+15 -1.627D+02 1.D+00 -4.606D+00 1.D+00 1.D+00 1.D+07 8.D-09  307P  0   0
 17 5.D+16 -1.627D+02 1.D+00 -4.606D+00 1.D+00 1.D+00 3.D+08 2.D-08  424P  0   0
 18 5.D+17 -1.627D+02 1.D+00 -4.606D+00 1.D+00 1.D+00 2.D+09 2.D-08  547P  0   0
 19 5.D+18 -1.627D+02 1.D+00 -4.606D+00 1.D+00 1.D+00 6.D+09 5.D-09  665P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 5.D+19 -1.627D+02 1.D+00 -4.606D+00 1.D+00 1.D+00 4.D+10 3.D-09  782P  0   0
 21 5.D+20 -1.627D+02 1.D+00 -4.606D+00 1.D+00 1.D+00 3.D+11 5.D-10  913P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.27

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   4626
 Subroutine evalg    (coded=T):    991
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  93037 (  4651 calls per constraint in average)
 Subroutine evaljac  (coded=T):  11306 (   565 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    911
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 70
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 3.5D-02
 Smallest constraints scale factor : 8.5D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -1.099D+02 3.D+00 -3.822D+00 2.D+00 2.D+00 1.D+00 2.D+00    0   0   0
  1 7.D+00 -2.261D+02 1.D+00 -7.866D+00 8.D-01 8.D-01 1.D+00 2.D-01   10C  0   0
  2 8.D+01 -1.667D+02 1.D+00 -5.798D+00 8.D-01 8.D-01 1.D-05 3.D-02   46C  0   0
  3 8.D+02 -1.274D+02 1.D+00 -4.431D+00 8.D-01 8.D-01 2.D-08 4.D-03   99C  0   0
  4 8.D+03 -1.284D+02 1.D+00 -4.468D+00 8.D-01 8.D-01 1.D-08 6.D-06  166C  0   0
  5 8.D+04 -1.284D+02 1.D+00 -4.467D+00 8.D-01 8.D-01 7.D-09 1.D-08  169C  0   0
  6 8.D+05 -1.284D+02 1.D+00 -4.467D+00 8.D-01 8.D-01 6.D-08 3.D-13  170C  0   0
  7 8.D+06 -1.284D+02 1.D+00 -4.467D+00 8.D-01 8.D-01 2.D-06 3.D-13  170C  0   0
  8 8.D+07 -1.284D+02 1.D+00 -4.467D+00 8.D-01 8.D-01 2.D-05 3.D-13  170C  0   0
  9 8.D+08 -1.284D+02 1.D+00 -4.467D+00 8.D-01 8.D-01 3.D-06 7.D-14  171C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 8.D+09 -1.284D+02 1.D+00 -4.467D+00 8.D-01 8.D-01 9.D-06 1.D-15  172C  0   0
 11 8.D+10 -1.284D+02 1.D+00 -4.467D+00 8.D-01 8.D-01 1.D-04 1.D-15  175C  0   0
 12 8.D+11 -1.284D+02 1.D+00 -4.467D+00 8.D-01 8.D-01 1.D-03 1.D-15  178P  0   0
 13 8.D+12 -1.284D+02 1.D+00 -4.467D+00 8.D-01 8.D-01 8.D+03 3.D-09  187P  0   0
 14 8.D+13 -1.284D+02 1.D+00 -4.467D+00 8.D-01 8.D-01 1.D+05 2.D-09  191P  0   0
 15 8.D+14 -1.284D+02 1.D+00 -4.467D+00 8.D-01 8.D-01 6.D+06 3.D-08  227P  0   0
 16 8.D+15 -1.284D+02 1.D+00 -4.467D+00 8.D-01 8.D-01 1.D+08 2.D-08  231P  0   0
 17 8.D+16 -1.284D+02 1.D+00 -4.467D+00 8.D-01 8.D-01 1.D+07 4.D-10  322P  0   0
 18 8.D+17 -1.284D+02 1.D+00 -4.467D+00 8.D-01 8.D-01 8.D+09 1.D-08  326P  0   0
 19 8.D+18 -1.284D+02 1.D+00 -4.467D+00 8.D-01 8.D-01 5.D+08 3.D-10  397P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 8.D+19 -1.284D+02 1.D+00 -4.467D+00 8.D-01 8.D-01 8.D+11 1.D-08  401P  0   0
 21 8.D+20 -1.284D+02 1.D+00 -4.467D+00 8.D-01 8.D-01 4.D+12 1.D-08  689P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.21

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   3250
 Subroutine evalg    (coded=T):    821
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  66597 (  3329 calls per constraint in average)
 Subroutine evaljac  (coded=T):   9887 (   494 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    686
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 71
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 3.4D-02
 Smallest constraints scale factor : 7.7D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -1.628D+02 4.D+00 -5.503D+00 2.D+00 2.D+00 9.D-01 8.D-01    0   0   0
  1 2.D+01 -2.545D+02 1.D+00 -8.602D+00 5.D-01 5.D-01 2.D+00 2.D-01   10C  0   0
  2 9.D+01 -2.055D+02 1.D+00 -6.944D+00 5.D-01 5.D-01 3.D-05 1.D-02   20C  0   0
  3 9.D+02 -2.043D+02 1.D+00 -6.905D+00 5.D-01 5.D-01 7.D-05 1.D-05   27C  0   0
  4 9.D+03 -2.043D+02 1.D+00 -6.905D+00 5.D-01 5.D-01 2.D-08 8.D-09   30C  0   0
  5 9.D+04 -2.043D+02 1.D+00 -6.905D+00 5.D-01 5.D-01 4.D-05 6.D-10   31C  0   0
  6 9.D+05 -2.043D+02 1.D+00 -6.905D+00 5.D-01 5.D-01 6.D-10 5.D-11   34C  0   0
  7 9.D+06 -2.043D+02 1.D+00 -6.905D+00 5.D-01 5.D-01 4.D-05 6.D-12   35C  0   0
  8 9.D+07 -2.043D+02 1.D+00 -6.905D+00 5.D-01 5.D-01 3.D-06 5.D-13   36C  0   0
  9 9.D+08 -2.043D+02 1.D+00 -6.905D+00 5.D-01 5.D-01 2.D-06 6.D-15   37C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 9.D+09 -2.043D+02 1.D+00 -6.905D+00 5.D-01 5.D-01 5.D-05 6.D-15   37C  0   0
 11 9.D+10 -2.043D+02 1.D+00 -6.905D+00 5.D-01 5.D-01 1.D-04 1.D-15   38C  0   0
 12 9.D+11 -2.043D+02 1.D+00 -6.905D+00 5.D-01 5.D-01 2.D+03 8.D-09   47P  0   0
 13 9.D+12 -2.043D+02 1.D+00 -6.905D+00 5.D-01 5.D-01 8.D+02 1.D-10   74P  0   0
 14 9.D+13 -2.043D+02 1.D+00 -6.905D+00 5.D-01 5.D-01 7.D+04 3.D-09   78P  0   0
 15 9.D+14 -2.043D+02 1.D+00 -6.905D+00 5.D-01 5.D-01 2.D+06 2.D-09   86P  0   0
 16 9.D+15 -2.043D+02 1.D+00 -6.905D+00 5.D-01 5.D-01 1.D+06 2.D-10  125P  0   0
 17 9.D+16 -2.043D+02 1.D+00 -6.905D+00 5.D-01 5.D-01 7.D+05 2.D-10  167P  0   0
 18 9.D+17 -2.043D+02 1.D+00 -6.905D+00 5.D-01 5.D-01 2.D+09 2.D-09  182P  0   0
 19 9.D+18 -2.043D+02 1.D+00 -6.905D+00 5.D-01 5.D-01 2.D+10 2.D-09  201P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 9.D+19 -2.043D+02 1.D+00 -6.905D+00 5.D-01 5.D-01 1.D+11 2.D-09  223P  0   0
 21 9.D+20 -2.043D+02 1.D+00 -6.905D+00 5.D-01 5.D-01 1.D+08 8.D-12  238P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.07

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   1306
 Subroutine evalg    (coded=T):    314
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  26568 (  1328 calls per constraint in average)
 Subroutine evaljac  (coded=T):   2970 (   148 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    237
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 72
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 5.4D-02
 Smallest constraints scale factor : 1.3D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -5.036D+01 3.D+00 -2.736D+00 2.D+00 2.D+00 1.D+00 2.D+00    0   0   0
  1 6.D+00 -4.199D+02 1.D+00 -2.281D+01 1.D+00 1.D+00 2.D+00 5.D-01   10C  0   0
  2 2.D+02 -2.480D+02 1.D+00 -1.347D+01 1.D+00 1.D+00 9.D-06 1.D-02   96C  0   0
  3 2.D+03 -2.436D+02 1.D+00 -1.324D+01 1.D+00 1.D+00 7.D-05 9.D-05  120C  0   0
  4 2.D+04 -2.436D+02 1.D+00 -1.324D+01 1.D+00 1.D+00 4.D-08 4.D-07  130C  0   0
  5 2.D+05 -2.436D+02 1.D+00 -1.324D+01 1.D+00 1.D+00 2.D-07 3.D-11  132C  0   0
  6 2.D+06 -2.436D+02 1.D+00 -1.324D+01 1.D+00 1.D+00 4.D-06 2.D-12  133C  0   0
  7 2.D+07 -2.436D+02 1.D+00 -1.324D+01 1.D+00 1.D+00 5.D-05 2.D-12  133C  0   0
  8 2.D+08 -2.436D+02 1.D+00 -1.324D+01 1.D+00 1.D+00 4.D-05 2.D-13  134C  0   0
  9 2.D+09 -2.436D+02 1.D+00 -1.324D+01 1.D+00 1.D+00 4.D-05 3.D-14  135C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 2.D+10 -2.436D+02 1.D+00 -1.324D+01 1.D+00 1.D+00 2.D-05 4.D-15  136C  0   0
 11 2.D+11 -2.436D+02 1.D+00 -1.324D+01 1.D+00 1.D+00 9.D-05 6.D-16  141C  0   0
 12 2.D+12 -2.436D+02 1.D+00 -1.324D+01 1.D+00 1.D+00 2.D-03 1.D-16  147P  0   0
 13 2.D+13 -2.436D+02 1.D+00 -1.324D+01 1.D+00 1.D+00 1.D-02 9.D-16  153P  0   0
 14 2.D+14 -2.436D+02 1.D+00 -1.324D+01 1.D+00 1.D+00 3.D-01 4.D-16  159P  0   0
 15 2.D+15 -2.436D+02 1.D+00 -1.324D+01 1.D+00 1.D+00 4.D+07 2.D-08  163P  0   0
 16 2.D+16 -2.436D+02 1.D+00 -1.324D+01 1.D+00 1.D+00 3.D+07 5.D-09  168P  0   0
 17 2.D+17 -2.436D+02 1.D+00 -1.324D+01 1.D+00 1.D+00 6.D+06 1.D-10  179P  0   0
 18 2.D+18 -2.436D+02 1.D+00 -1.324D+01 1.D+00 1.D+00 1.D+10 7.D-09  212P  0   0
 19 2.D+19 -2.436D+02 1.D+00 -1.324D+01 1.D+00 1.D+00 2.D+07 7.D-13  342P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 2.D+20 -2.436D+02 1.D+00 -1.324D+01 1.D+00 1.D+00 8.D+11 5.D-09  347P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.09

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   1600
 Subroutine evalg    (coded=T):    467
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  33363 (  1668 calls per constraint in average)
 Subroutine evaljac  (coded=T):   5605 (   280 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    345
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 73
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 5.3D-02
 Smallest constraints scale factor : 1.2D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -4.282D+01 4.D+00 -2.277D+00 4.D+00 4.D+00 1.D+00 5.D+00    0   0   0
  1 1.D+00 -1.506D+03 4.D+00 -8.012D+01 4.D+00 4.D+00 1.D+00 4.D+00   10C  0   0
  2 3.D+01 -3.119D+02 1.D+00 -1.659D+01 1.D+00 1.D+00 2.D-06 6.D-02   34C  0   0
  3 3.D+01 -3.033D+02 1.D+00 -1.613D+01 1.D+00 1.D+00 7.D-06 6.D-02   47C  0   0
  4 3.D+02 -2.978D+02 1.D+00 -1.584D+01 1.D+00 1.D+00 2.D-06 2.D-03   59C  0   0
  5 3.D+03 -2.978D+02 1.D+00 -1.584D+01 1.D+00 1.D+00 5.D-09 1.D-05   64C  0   0
  6 3.D+04 -2.978D+02 1.D+00 -1.584D+01 1.D+00 1.D+00 2.D-09 1.D-08   67C  0   0
  7 3.D+05 -2.978D+02 1.D+00 -1.584D+01 1.D+00 1.D+00 7.D-08 1.D-13   76C  0   0
  8 3.D+06 -2.978D+02 1.D+00 -1.584D+01 1.D+00 1.D+00 5.D-07 1.D-13   76C  0   0
  9 3.D+07 -2.978D+02 1.D+00 -1.584D+01 1.D+00 1.D+00 5.D-06 1.D-13   76C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 3.D+08 -2.978D+02 1.D+00 -1.584D+01 1.D+00 1.D+00 5.D-05 1.D-13   76C  0   0
 11 3.D+09 -2.978D+02 1.D+00 -1.584D+01 1.D+00 1.D+00 2.D-05 2.D-14   77C  0   0
 12 3.D+10 -2.978D+02 1.D+00 -1.584D+01 1.D+00 1.D+00 2.D-05 6.D-16   78C  0   0
 13 3.D+11 -2.978D+02 1.D+00 -1.584D+01 1.D+00 1.D+00 2.D-05 7.D-17   83C  0   0
 14 3.D+12 -2.978D+02 1.D+00 -1.584D+01 1.D+00 1.D+00 2.D-05 0.D+00   86C  0   0
 15 3.D+13 -2.978D+02 1.D+00 -1.584D+01 1.D+00 1.D+00 2.D-05 0.D+00   86C  0   0
 16 3.D+14 -2.978D+02 1.D+00 -1.584D+01 1.D+00 1.D+00 2.D-05 0.D+00   86C  0   0
 17 3.D+15 -2.978D+02 1.D+00 -1.584D+01 1.D+00 1.D+00 2.D-05 0.D+00   86C  0   0
 18 3.D+16 -2.978D+02 1.D+00 -1.584D+01 1.D+00 1.D+00 2.D-05 0.D+00   86C  0   0
 19 3.D+17 -2.978D+02 1.D+00 -1.584D+01 1.D+00 1.D+00 2.D-05 0.D+00   86C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 3.D+18 -2.978D+02 1.D+00 -1.584D+01 1.D+00 1.D+00 2.D-05 0.D+00   86C  0   0
 21 3.D+19 -2.978D+02 1.D+00 -1.584D+01 1.D+00 1.D+00 2.D-05 0.D+00   86C  0   0
 22 3.D+20 -2.978D+02 1.D+00 -1.584D+01 1.D+00 1.D+00 2.D-05 0.D+00   86C  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.01

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):    210
 Subroutine evalg    (coded=T):    167
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):   4727 (   236 calls per constraint in average)
 Subroutine evaljac  (coded=T):   2139 (   106 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):     85
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 74
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 4.4D-02
 Smallest constraints scale factor : 1.3D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -6.544D+01 3.D+00 -2.867D+00 1.D+00 1.D+00 1.D+00 1.D+00    0   0   0
  1 7.D+00 -4.552D+02 1.D+00 -1.994D+01 1.D+00 1.D+00 1.D+00 4.D-01   10C  0   0
  2 1.D+02 -2.451D+02 1.D+00 -1.074D+01 1.D+00 1.D+00 2.D-07 1.D-02   40C  0   0
  3 1.D+03 -2.438D+02 1.D+00 -1.068D+01 1.D+00 1.D+00 4.D-05 3.D-05   59C  0   0
  4 1.D+04 -2.438D+02 1.D+00 -1.068D+01 1.D+00 1.D+00 4.D-05 7.D-09   61C  0   0
  5 1.D+05 -2.438D+02 1.D+00 -1.068D+01 1.D+00 1.D+00 9.D-05 4.D-10   63C  0   0
  6 1.D+06 -2.438D+02 1.D+00 -1.068D+01 1.D+00 1.D+00 8.D-06 8.D-11   64C  0   0
  7 1.D+07 -2.438D+02 1.D+00 -1.068D+01 1.D+00 1.D+00 9.D-06 1.D-12   65C  0   0
  8 1.D+08 -2.438D+02 1.D+00 -1.068D+01 1.D+00 1.D+00 1.D-05 1.D-13   66C  0   0
  9 1.D+09 -2.438D+02 1.D+00 -1.068D+01 1.D+00 1.D+00 2.D-05 3.D-14   67C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 1.D+10 -2.438D+02 1.D+00 -1.068D+01 1.D+00 1.D+00 2.D-06 6.D-16   68C  0   0
 11 1.D+11 -2.438D+02 1.D+00 -1.068D+01 1.D+00 1.D+00 4.D-05 4.D-16   71C  0   0
 12 1.D+12 -2.438D+02 1.D+00 -1.068D+01 1.D+00 1.D+00 8.D-04 7.D-17   74P  0   0
 13 1.D+13 -1.722D+02 1.D+00 -7.544D+00 1.D+00 1.D+00 1.D+00 1.D-13 1074M  0   0
 14 1.D+14 -1.722D+02 1.D+00 -7.544D+00 1.D+00 1.D+00 6.D+04 7.D-10 1078P  0   0
 15 1.D+15 -1.722D+02 1.D+00 -7.544D+00 1.D+00 1.D+00 1.D+05 1.D-10 1092P  0   0
 16 1.D+16 -1.722D+02 1.D+00 -7.544D+00 1.D+00 1.D+00 6.D+06 7.D-10 1097P  0   0
 17 1.D+17 -1.722D+02 1.D+00 -7.544D+00 1.D+00 1.D+00 4.D+06 3.D-12 1106P  0   0
 18 1.D+18 -1.722D+02 1.D+00 -7.544D+00 1.D+00 1.D+00 6.D+07 7.D-11 1117P  0   0
 19 1.D+19 -1.722D+02 1.D+00 -7.544D+00 1.D+00 1.D+00 9.D+06 3.D-12 1122P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 1.D+20 -1.722D+02 1.D+00 -7.544D+00 1.D+00 1.D+00 2.D+10 3.D-10 1129P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.19

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   3575
 Subroutine evalg    (coded=T):   2200
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  91931 (  4596 calls per constraint in average)
 Subroutine evaljac  (coded=T):  20123 (  1006 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):   1127
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 75
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 3.5D-02
 Smallest constraints scale factor : 9.7D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -1.337D+02 4.D+00 -4.668D+00 4.D+00 4.D+00 1.D+00 3.D+00    0   0   0
  1 6.D+00 -3.816D+02 1.D+00 -1.333D+01 1.D+00 1.D+00 8.D-01 3.D-01   10C  0   0
  2 9.D+01 -2.599D+02 1.D+00 -9.075D+00 1.D+00 1.D+00 2.D-05 8.D-03   51C  0   0
  3 9.D+02 -2.559D+02 1.D+00 -8.937D+00 1.D+00 1.D+00 2.D-06 6.D-05   62C  0   0
  4 9.D+03 -2.559D+02 1.D+00 -8.937D+00 1.D+00 1.D+00 3.D-10 2.D-08   65C  0   0
  5 9.D+04 -2.559D+02 1.D+00 -8.937D+00 1.D+00 1.D+00 7.D-05 8.D-10   66C  0   0
  6 9.D+05 -2.559D+02 1.D+00 -8.937D+00 1.D+00 1.D+00 7.D-07 1.D-10   67C  0   0
  7 9.D+06 -2.559D+02 1.D+00 -8.937D+00 1.D+00 1.D+00 6.D-07 1.D-14   68C  0   0
  8 9.D+07 -2.559D+02 1.D+00 -8.937D+00 1.D+00 1.D+00 5.D-07 1.D-14   68C  0   0
  9 9.D+08 -2.559D+02 1.D+00 -8.937D+00 1.D+00 1.D+00 7.D-06 1.D-14   68C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 9.D+09 -2.559D+02 1.D+00 -8.937D+00 1.D+00 1.D+00 7.D-05 1.D-14   68C  0   0
 11 9.D+10 -2.559D+02 1.D+00 -8.937D+00 1.D+00 1.D+00 3.D+03 3.D-08   77P  0   0
 12 9.D+11 -2.559D+02 1.D+00 -8.937D+00 1.D+00 1.D+00 8.D-04 3.D-11   84P  0   0
 13 9.D+12 -2.559D+02 1.D+00 -8.937D+00 1.D+00 1.D+00 4.D+05 4.D-08   89P  0   0
 14 9.D+13 -2.559D+02 1.D+00 -8.937D+00 1.D+00 1.D+00 2.D+04 3.D-10  292P  0   0
 15 9.D+14 -2.559D+02 1.D+00 -8.937D+00 1.D+00 1.D+00 4.D+07 5.D-08  297P  0   0
 16 9.D+15 -2.559D+02 1.D+00 -8.937D+00 1.D+00 1.D+00 4.D+06 4.D-10  418P  0   0
 17 9.D+16 -2.559D+02 1.D+00 -8.937D+00 1.D+00 1.D+00 2.D+09 3.D-08  424P  0   0
 18 9.D+17 -2.559D+02 1.D+00 -8.937D+00 1.D+00 1.D+00 3.D+07 3.D-11  716P  0   0
 19 9.D+18 -2.559D+02 1.D+00 -8.937D+00 1.D+00 1.D+00 3.D+11 3.D-08  723P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 9.D+19 -2.559D+02 1.D+00 -8.937D+00 1.D+00 1.D+00 6.D+09 7.D-11  998P  0   0
 21 9.D+20 -2.559D+02 1.D+00 -8.937D+00 1.D+00 1.D+00 3.D+13 3.D-08 1005P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.25

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   4916
 Subroutine evalg    (coded=T):   1096
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  99122 (  4956 calls per constraint in average)
 Subroutine evaljac  (coded=T):  12427 (   621 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):   1004
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 76
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 4.0D-02
 Smallest constraints scale factor : 9.1D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -9.315D+01 3.D+00 -3.772D+00 1.D+00 1.D+00 9.D-01 9.D-01    0   0   0
  1 1.D+01 -2.025D+02 1.D+00 -8.201D+00 1.D+00 1.D+00 1.D+00 1.D-01   10C  0   0
  2 8.D+01 -1.588D+02 1.D+00 -6.431D+00 1.D+00 1.D+00 4.D-05 2.D-02   20C  0   0
  3 8.D+02 -1.560D+02 1.D+00 -6.317D+00 1.D+00 1.D+00 3.D-05 2.D-05   29C  0   0
  4 8.D+03 -1.560D+02 1.D+00 -6.318D+00 1.D+00 1.D+00 6.D-05 7.D-09   48C  0   0
  5 8.D+04 -1.560D+02 1.D+00 -6.318D+00 1.D+00 1.D+00 7.D-05 1.D-09   49C  0   0
  6 8.D+05 -1.560D+02 1.D+00 -6.318D+00 1.D+00 1.D+00 7.D-05 1.D-10   50C  0   0
  7 8.D+06 -1.560D+02 1.D+00 -6.318D+00 1.D+00 1.D+00 5.D-05 8.D-12   51C  0   0
  8 8.D+07 -1.560D+02 1.D+00 -6.318D+00 1.D+00 1.D+00 2.D-08 4.D-12   67C  0   0
  9 8.D+08 -1.560D+02 1.D+00 -6.318D+00 1.D+00 1.D+00 2.D-05 4.D-12   68C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 8.D+09 -1.560D+02 1.D+00 -6.318D+00 1.D+00 1.D+00 2.D-05 4.D-12   69C  0   0
 11 8.D+10 -1.560D+02 1.D+00 -6.318D+00 1.D+00 1.D+00 2.D-05 2.D-13  534C  0   0
 12 8.D+11 -1.560D+02 1.D+00 -6.318D+00 1.D+00 1.D+00 6.D-04 3.D-16  659P  0   0
 13 8.D+12 -1.560D+02 1.D+00 -6.318D+00 1.D+00 1.D+00 7.D-03 1.D-16  662P  0   0
 14 8.D+13 -1.560D+02 1.D+00 -6.318D+00 1.D+00 1.D+00 9.D-02 1.D-15  665P  0   0
 15 8.D+14 -1.560D+02 1.D+00 -6.318D+00 1.D+00 1.D+00 2.D+00 2.D-15  710P  0   0
 16 8.D+15 -1.560D+02 1.D+00 -6.318D+00 1.D+00 1.D+00 7.D-01 4.D-16  825P  0   0
 17 8.D+16 -1.560D+02 1.D+00 -6.318D+00 1.D+00 1.D+00 2.D+01 2.D-16  836P  0   0
 18 8.D+17 -1.560D+02 1.D+00 -6.318D+00 1.D+00 1.D+00 2.D+03 3.D-15  839P  0   0
 19 8.D+18 -1.560D+02 1.D+00 -6.318D+00 1.D+00 1.D+00 9.D+01 0.D+00  850P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 8.D+19 -1.560D+02 1.D+00 -6.318D+00 1.D+00 1.D+00 5.D+03 9.D-17  859P  0   0
 21 8.D+20 -1.560D+02 1.D+00 -6.318D+00 1.D+00 1.D+00 7.D+04 2.D-16  862P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.17

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   4087
 Subroutine evalg    (coded=T):    985
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  82827 (  4141 calls per constraint in average)
 Subroutine evaljac  (coded=T):  10611 (   530 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    864
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 77
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 2.9D-02
 Smallest constraints scale factor : 8.5D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -1.120D+02 4.D+00 -3.279D+00 4.D+00 4.D+00 9.D-01 2.D+00    0   0   0
  1 3.D+00 -3.802D+02 1.D+00 -1.113D+01 9.D-01 9.D-01 7.D-01 6.D-01   10C  0   0
  2 1.D+02 -2.538D+02 1.D+00 -7.429D+00 6.D-01 6.D-01 1.D-09 1.D-02  115C  0   0
  3 1.D+03 -2.494D+02 1.D+00 -7.301D+00 6.D-01 6.D-01 3.D-05 1.D-05  124C  0   0
  4 1.D+04 -2.494D+02 1.D+00 -7.301D+00 6.D-01 6.D-01 7.D-06 2.D-09  126C  0   0
  5 1.D+05 -2.494D+02 1.D+00 -7.301D+00 6.D-01 6.D-01 3.D-05 1.D-10  127C  0   0
  6 1.D+06 -2.494D+02 1.D+00 -7.301D+00 6.D-01 6.D-01 2.D-05 2.D-11  128C  0   0
  7 1.D+07 -2.494D+02 1.D+00 -7.301D+00 6.D-01 6.D-01 2.D-07 3.D-12  129C  0   0
  8 1.D+08 -2.494D+02 1.D+00 -7.301D+00 6.D-01 6.D-01 5.D-06 5.D-14  130C  0   0
  9 1.D+09 -2.494D+02 1.D+00 -7.301D+00 6.D-01 6.D-01 5.D-05 5.D-14  130C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 1.D+10 -2.494D+02 1.D+00 -7.301D+00 6.D-01 6.D-01 2.D-05 7.D-15  131C  0   0
 11 1.D+11 -2.494D+02 1.D+00 -7.301D+00 6.D-01 6.D-01 6.D-05 2.D-16  132C  0   0
 12 1.D+12 -2.494D+02 1.D+00 -7.301D+00 6.D-01 6.D-01 1.D-03 1.D-15  138P  0   0
 13 1.D+13 -2.494D+02 1.D+00 -7.301D+00 6.D-01 6.D-01 3.D-03 2.D-16  142P  0   0
 14 1.D+14 -2.494D+02 1.D+00 -7.301D+00 6.D-01 6.D-01 1.D-01 1.D-15  145P  0   0
 15 1.D+15 -2.494D+02 1.D+00 -7.301D+00 6.D-01 6.D-01 9.D+04 9.D-11  192P  0   0
 16 1.D+16 -2.494D+02 1.D+00 -7.301D+00 6.D-01 6.D-01 3.D+07 3.D-09  196P  0   0
 17 1.D+17 -2.494D+02 1.D+00 -7.301D+00 6.D-01 6.D-01 2.D+06 6.D-12  218P  0   0
 18 1.D+18 -2.494D+02 1.D+00 -7.301D+00 6.D-01 6.D-01 1.D+09 4.D-09  222P  0   0
 19 1.D+19 -2.494D+02 1.D+00 -7.301D+00 6.D-01 6.D-01 6.D+10 2.D-08  230P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 1.D+20 -2.494D+02 1.D+00 -7.301D+00 6.D-01 6.D-01 1.D+12 1.D-08  259P  0   0
 21 1.D+21 -2.494D+02 1.D+00 -7.301D+00 6.D-01 6.D-01 6.D+12 2.D-08  511P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.11

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   2511
 Subroutine evalg    (coded=T):    636
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  51675 (  2583 calls per constraint in average)
 Subroutine evaljac  (coded=T):   6953 (   347 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    509
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 78
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 2.2D-02
 Smallest constraints scale factor : 5.3D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -2.115D+02 3.D+00 -4.646D+00 1.D+00 1.D+00 8.D-01 8.D-01    0   0   0
  1 2.D+01 -2.430D+02 1.D+00 -5.337D+00 1.D+00 1.D+00 1.D+00 6.D-02   10C  0   0
  2 4.D+01 -2.114D+02 1.D+00 -4.644D+00 1.D+00 1.D+00 6.D-06 2.D-02   30C  0   0
  3 4.D+02 -2.099D+02 1.D+00 -4.611D+00 1.D+00 1.D+00 9.D-09 4.D-05   36C  0   0
  4 4.D+03 -2.099D+02 1.D+00 -4.611D+00 1.D+00 1.D+00 6.D-09 4.D-08   39C  0   0
  5 4.D+04 -2.099D+02 1.D+00 -4.611D+00 1.D+00 1.D+00 5.D-05 3.D-10   41C  0   0
  6 4.D+05 -2.099D+02 1.D+00 -4.611D+00 1.D+00 1.D+00 1.D-05 1.D-10   42C  0   0
  7 4.D+06 -2.099D+02 1.D+00 -4.611D+00 1.D+00 1.D+00 3.D-05 9.D-12   43C  0   0
  8 4.D+07 -2.099D+02 1.D+00 -4.611D+00 1.D+00 1.D+00 3.D-05 1.D-12   44C  0   0
  9 4.D+08 -2.099D+02 1.D+00 -4.611D+00 1.D+00 1.D+00 3.D-05 1.D-13   45C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 4.D+09 -2.099D+02 1.D+00 -4.611D+00 1.D+00 1.D+00 4.D-05 1.D-14   46C  0   0
 11 4.D+10 -2.099D+02 1.D+00 -4.611D+00 1.D+00 1.D+00 4.D-05 1.D-15   47C  0   0
 12 4.D+11 -2.099D+02 1.D+00 -4.611D+00 1.D+00 1.D+00 8.D-05 2.D-16   48C  0   0
 13 4.D+12 -2.099D+02 1.D+00 -4.611D+00 1.D+00 1.D+00 3.D-03 5.D-16   55P  0   0
 14 4.D+13 -2.099D+02 1.D+00 -4.611D+00 1.D+00 1.D+00 3.D-02 7.D-16   65P  0   0
 15 4.D+14 -2.099D+02 1.D+00 -4.611D+00 1.D+00 1.D+00 1.D-01 5.D-16   72P  0   0
 16 4.D+15 -2.099D+02 1.D+00 -4.611D+00 1.D+00 1.D+00 3.D+07 9.D-09   78P  0   0
 17 4.D+16 -2.099D+02 1.D+00 -4.611D+00 1.D+00 1.D+00 5.D+08 3.D-08  197P  0   0
 18 4.D+17 -2.099D+02 1.D+00 -4.611D+00 1.D+00 1.D+00 3.D+09 9.D-09  463P  0   0
 19 4.D+18 -2.099D+02 1.D+00 -4.611D+00 1.D+00 1.D+00 2.D+10 1.D-08  752P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 4.D+19 -2.099D+02 1.D+00 -4.611D+00 1.D+00 1.D+00 3.D+11 9.D-09  767P  0   0
 21 4.D+20 -2.099D+02 1.D+00 -4.611D+00 1.D+00 1.D+00 3.D+12 6.D-09 1391P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.39

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   6957
 Subroutine evalg    (coded=T):   1465
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T): 139563 (  6978 calls per constraint in average)
 Subroutine evaljac  (coded=T):  16197 (   809 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):   1389
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 79
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 2.0D-02
 Smallest constraints scale factor : 6.1D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -1.910D+02 4.D+00 -3.739D+00 4.D+00 4.D+00 7.D-01 3.D+00    0   0   0
  1 4.D+00 -3.835D+02 1.D+00 -7.508D+00 7.D-01 7.D-01 1.D+00 3.D-01   10C  0   0
  2 8.D+01 -2.404D+02 1.D+00 -4.708D+00 7.D-01 7.D-01 4.D-08 6.D-03   40C  0   0
  3 8.D+02 -2.379D+02 1.D+00 -4.658D+00 7.D-01 7.D-01 1.D-05 2.D-05   47C  0   0
  4 8.D+03 -2.379D+02 1.D+00 -4.658D+00 7.D-01 7.D-01 2.D-05 2.D-08   49C  0   0
  5 8.D+04 -2.379D+02 1.D+00 -4.658D+00 7.D-01 7.D-01 9.D-06 2.D-10   50C  0   0
  6 8.D+05 -2.379D+02 1.D+00 -4.658D+00 7.D-01 7.D-01 1.D-05 2.D-11   51C  0   0
  7 8.D+06 -2.379D+02 1.D+00 -4.658D+00 7.D-01 7.D-01 2.D-05 2.D-12   52C  0   0
  8 8.D+07 -2.379D+02 1.D+00 -4.658D+00 7.D-01 7.D-01 9.D-06 3.D-13   53C  0   0
  9 8.D+08 -2.379D+02 1.D+00 -4.658D+00 7.D-01 7.D-01 8.D-05 3.D-13   53C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 8.D+09 -2.379D+02 1.D+00 -4.658D+00 7.D-01 7.D-01 9.D-06 1.D-14   54C  0   0
 11 8.D+10 -2.379D+02 1.D+00 -4.658D+00 7.D-01 7.D-01 6.D-05 8.D-16   55C  0   0
 12 8.D+11 -2.379D+02 1.D+00 -4.658D+00 7.D-01 7.D-01 8.D-05 1.D-16   56C  0   0
 13 8.D+12 -2.379D+02 1.D+00 -4.658D+00 7.D-01 7.D-01 2.D-02 3.D-15   59P  0   0
 14 8.D+13 -2.379D+02 1.D+00 -4.658D+00 7.D-01 7.D-01 2.D+03 2.D-11  136P  0   0
 15 8.D+14 -2.379D+02 1.D+00 -4.658D+00 7.D-01 7.D-01 7.D+06 1.D-08  141P  0   0
 16 8.D+15 -2.379D+02 1.D+00 -4.658D+00 7.D-01 7.D-01 4.D+07 5.D-09  201P  0   0
 17 8.D+16 -2.379D+02 1.D+00 -4.658D+00 7.D-01 7.D-01 2.D+06 3.D-11  308P  0   0
 18 8.D+17 -2.379D+02 1.D+00 -4.658D+00 7.D-01 7.D-01 8.D+07 1.D-10  312P  0   0
 19 8.D+18 -2.379D+02 1.D+00 -4.658D+00 7.D-01 7.D-01 4.D+10 6.D-09  326P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 8.D+19 -2.379D+02 1.D+00 -4.658D+00 7.D-01 7.D-01 4.D+11 5.D-09  369P  0   0
 21 8.D+20 -2.379D+02 1.D+00 -4.658D+00 7.D-01 7.D-01 4.D+12 5.D-09  409P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.09

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   1724
 Subroutine evalg    (coded=T):    492
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  35040 (  1752 calls per constraint in average)
 Subroutine evaljac  (coded=T):   5506 (   275 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    415
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 80
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 6.4D-02
 Smallest constraints scale factor : 1.5D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -4.237D+01 3.D+00 -2.702D+00 2.D+00 2.D+00 1.D+00 2.D+00    0   0   0
  1 5.D+00 -3.561D+02 1.D+00 -2.271D+01 1.D+00 1.D+00 4.D+00 1.D+00   10C  0   0
  2 2.D+02 -1.845D+02 1.D+00 -1.177D+01 3.D-01 3.D-01 2.D-05 9.D-03   53C  0   0
  3 2.D+02 -1.840D+02 1.D+00 -1.174D+01 3.D-01 3.D-01 2.D-07 1.D-04   62C  0   0
  4 2.D+03 -1.840D+02 1.D+00 -1.174D+01 3.D-01 3.D-01 8.D-06 2.D-06   66C  0   0
  5 2.D+04 -1.840D+02 1.D+00 -1.174D+01 3.D-01 3.D-01 1.D-04 2.D-06   67C  0   0
  6 2.D+05 -1.840D+02 1.D+00 -1.174D+01 3.D-01 3.D-01 5.D-05 6.D-07   69C  0   0
  7 2.D+06 -1.840D+02 1.D+00 -1.174D+01 3.D-01 3.D-01 3.D-05 4.D-10  249C  0   0
  8 2.D+07 -1.840D+02 1.D+00 -1.174D+01 3.D-01 3.D-01 8.D-07 8.D-11  251C  0   0
  9 2.D+08 -1.840D+02 1.D+00 -1.174D+01 3.D-01 3.D-01 1.D-05 8.D-11  252C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 2.D+09 -1.840D+02 1.D+00 -1.174D+01 3.D-01 3.D-01 8.D-07 6.D-11  262C  0   0
 11 2.D+10 -1.840D+02 1.D+00 -1.174D+01 3.D-01 3.D-01 2.D+02 2.D-08  297P  0   0
 12 2.D+11 -1.840D+02 1.D+00 -1.174D+01 3.D-01 3.D-01 5.D+02 3.D-09  345P  0   0
 13 2.D+12 -1.840D+02 1.D+00 -1.174D+01 3.D-01 3.D-01 6.D+02 3.D-10  379P  0   0
 14 2.D+13 -1.840D+02 1.D+00 -1.174D+01 3.D-01 3.D-01 2.D+04 2.D-09  383P  0   0
 15 2.D+14 -1.840D+02 1.D+00 -1.174D+01 3.D-01 3.D-01 5.D+05 3.D-09  400P  0   0
 16 2.D+15 -1.840D+02 1.D+00 -1.174D+01 3.D-01 3.D-01 4.D+06 3.D-09  451P  0   0
 17 2.D+16 -1.840D+02 1.D+00 -1.174D+01 3.D-01 3.D-01 4.D+07 9.D-09  472P  0   0
 18 2.D+17 -1.840D+02 1.D+00 -1.174D+01 3.D-01 3.D-01 4.D+08 8.D-09  525P  0   0
 19 2.D+18 -1.840D+02 1.D+00 -1.174D+01 3.D-01 3.D-01 9.D+08 1.D-09  572P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 2.D+19 -1.840D+02 1.D+00 -1.174D+01 3.D-01 3.D-01 4.D+10 6.D-09  580P  0   0
 21 2.D+20 -1.840D+02 1.D+00 -1.174D+01 3.D-01 3.D-01 3.D+09 6.D-12  598P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.12

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   2285
 Subroutine evalg    (coded=T):    758
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  47841 (  2392 calls per constraint in average)
 Subroutine evaljac  (coded=T):   9135 (   456 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    602
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 81
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 1.9D-02
 Smallest constraints scale factor : 6.4D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -2.107D+02 4.D+00 -4.083D+00 4.D+00 4.D+00 6.D-01 5.D+00    0   0   0
  1 3.D+00 -4.511D+02 1.D+00 -8.742D+00 1.D+00 1.D+00 9.D-01 6.D-01   10C  0   0
  2 5.D+01 -2.516D+02 1.D+00 -4.874D+00 1.D+00 1.D+00 8.D-05 2.D-02  102C  0   0
  3 5.D+02 -2.486D+02 1.D+00 -4.818D+00 1.D+00 1.D+00 2.D-05 3.D-05  122C  0   0
  4 5.D+03 -2.486D+02 1.D+00 -4.818D+00 1.D+00 1.D+00 3.D-07 1.D-08  125C  0   0
  5 5.D+04 -2.486D+02 1.D+00 -4.818D+00 1.D+00 1.D+00 4.D-07 7.D-12  126C  0   0
  6 5.D+05 -2.486D+02 1.D+00 -4.818D+00 1.D+00 1.D+00 4.D-06 7.D-12  126C  0   0
  7 5.D+06 -2.486D+02 1.D+00 -4.818D+00 1.D+00 1.D+00 4.D-05 7.D-12  126C  0   0
  8 5.D+07 -2.486D+02 1.D+00 -4.818D+00 1.D+00 1.D+00 2.D-05 5.D-13  127C  0   0
  9 5.D+08 -2.486D+02 1.D+00 -4.818D+00 1.D+00 1.D+00 2.D-05 6.D-14  128C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 5.D+09 -2.486D+02 1.D+00 -4.818D+00 1.D+00 1.D+00 3.D-05 6.D-15  129C  0   0
 11 5.D+10 -2.486D+02 1.D+00 -4.818D+00 1.D+00 1.D+00 6.D-05 1.D-15  130C  0   0
 12 5.D+11 -2.486D+02 1.D+00 -4.818D+00 1.D+00 1.D+00 8.D-04 2.D-15  136P  0   0
 13 5.D+12 -2.486D+02 1.D+00 -4.818D+00 1.D+00 1.D+00 4.D+04 2.D-08  143P  0   0
 14 5.D+13 -2.486D+02 1.D+00 -4.818D+00 1.D+00 1.D+00 5.D+03 2.D-10  147P  0   0
 15 5.D+14 -2.486D+02 1.D+00 -4.818D+00 1.D+00 1.D+00 8.D+06 5.D-08  151P  0   0
 16 5.D+15 -2.486D+02 1.D+00 -4.818D+00 1.D+00 1.D+00 1.D+06 5.D-10  155P  0   0
 17 5.D+16 -2.486D+02 1.D+00 -4.818D+00 1.D+00 1.D+00 4.D+08 2.D-08  159P  0   0
 18 5.D+17 -2.486D+02 1.D+00 -4.818D+00 1.D+00 1.D+00 8.D+07 2.D-10  167P  0   0
 19 5.D+18 -2.486D+02 1.D+00 -4.818D+00 1.D+00 1.D+00 5.D+10 3.D-08  171P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 5.D+19 -2.486D+02 1.D+00 -4.818D+00 1.D+00 1.D+00 8.D+09 3.D-10  175P  0   0
 21 5.D+20 -2.486D+02 1.D+00 -4.818D+00 1.D+00 1.D+00 6.D+12 4.D-08  179P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.05

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):    818
 Subroutine evalg    (coded=T):    307
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  17881 (   894 calls per constraint in average)
 Subroutine evaljac  (coded=T):   3546 (   177 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    177
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 82
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 2.4D-02
 Smallest constraints scale factor : 7.3D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -9.987D+01 4.D+00 -2.378D+00 3.D+00 3.D+00 7.D-01 4.D+00    0   0   0
  1 2.D+00 -6.570D+02 4.D+00 -1.564D+01 1.D+00 1.D+00 7.D-01 7.D-01   10C  0   0
  2 6.D+01 -2.736D+02 1.D+00 -6.515D+00 1.D+00 1.D+00 1.D-05 9.D-03   24C  0   0
  3 6.D+02 -2.722D+02 1.D+00 -6.481D+00 1.D+00 1.D+00 5.D-05 6.D-05   34C  0   0
  4 6.D+03 -2.722D+02 1.D+00 -6.481D+00 1.D+00 1.D+00 3.D-08 1.D-07   37C  0   0
  5 6.D+04 -2.722D+02 1.D+00 -6.481D+00 1.D+00 1.D+00 8.D-08 3.D-11   39C  0   0
  6 6.D+05 -2.722D+02 1.D+00 -6.481D+00 1.D+00 1.D+00 2.D-05 3.D-11   39C  0   0
  7 6.D+06 -2.722D+02 1.D+00 -6.481D+00 1.D+00 1.D+00 6.D-06 4.D-12   40C  0   0
  8 6.D+07 -2.722D+02 1.D+00 -6.481D+00 1.D+00 1.D+00 2.D-05 4.D-13   41C  0   0
  9 6.D+08 -2.722D+02 1.D+00 -6.481D+00 1.D+00 1.D+00 4.D-07 3.D-14   42C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 6.D+09 -2.722D+02 1.D+00 -6.481D+00 1.D+00 1.D+00 3.D-06 1.D-16   43C  0   0
 11 6.D+10 -2.722D+02 1.D+00 -6.481D+00 1.D+00 1.D+00 4.D-05 1.D-16   43C  0   0
 12 6.D+11 -2.722D+02 1.D+00 -6.481D+00 1.D+00 1.D+00 5.D-04 8.D-16   48P  0   0
 13 6.D+12 -2.722D+02 1.D+00 -6.481D+00 1.D+00 1.D+00 2.D-03 3.D-16   53P  0   0
 14 6.D+13 -2.722D+02 1.D+00 -6.481D+00 1.D+00 1.D+00 5.D-02 8.D-16   56P  0   0
 15 6.D+14 -2.722D+02 1.D+00 -6.481D+00 1.D+00 1.D+00 2.D-01 3.D-16   61P  0   0
 16 6.D+15 -2.722D+02 1.D+00 -6.481D+00 1.D+00 1.D+00 5.D+00 8.D-16   64P  0   0
 17 6.D+16 -2.722D+02 1.D+00 -6.481D+00 1.D+00 1.D+00 8.D+07 1.D-09   69P  0   0
 18 6.D+17 -2.722D+02 1.D+00 -6.481D+00 1.D+00 1.D+00 2.D+09 3.D-09   76P  0   0
 19 6.D+18 -2.722D+02 1.D+00 -6.481D+00 1.D+00 1.D+00 7.D+09 9.D-10   81P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 6.D+19 -2.722D+02 1.D+00 -6.481D+00 1.D+00 1.D+00 1.D+11 2.D-09   87P  0   0
 21 6.D+20 -2.722D+02 1.D+00 -6.481D+00 1.D+00 1.D+00 9.D+11 1.D-09   92P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.02

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):    328
 Subroutine evalg    (coded=T):    176
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):   7112 (   355 calls per constraint in average)
 Subroutine evaljac  (coded=T):   2238 (   111 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):     92
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 83
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 3.9D-02
 Smallest constraints scale factor : 9.3D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -1.276D+02 4.D+00 -4.958D+00 2.D+00 2.D+00 1.D+00 3.D+00    0   0   0
  1 8.D+00 -3.144D+02 1.D+00 -1.221D+01 6.D-01 6.D-01 4.D-01 3.D-01   10C  0   0
  2 1.D+02 -1.775D+02 1.D+00 -6.897D+00 3.D-01 3.D-01 1.D-07 5.D-03   92C  0   0
  3 1.D+03 -1.785D+02 1.D+00 -6.936D+00 3.D-01 3.D-01 1.D-05 3.D-06  145C  0   0
  4 1.D+04 -1.785D+02 1.D+00 -6.936D+00 3.D-01 3.D-01 1.D-05 6.D-10  148C  0   0
  5 1.D+05 -1.785D+02 1.D+00 -6.936D+00 3.D-01 3.D-01 6.D-05 6.D-10  148C  0   0
  6 1.D+06 -1.785D+02 1.D+00 -6.936D+00 3.D-01 3.D-01 1.D-05 4.D-11  152C  0   0
  7 1.D+07 -1.785D+02 1.D+00 -6.936D+00 3.D-01 3.D-01 8.D-05 7.D-12  154C  0   0
  8 1.D+08 -1.785D+02 1.D+00 -6.936D+00 3.D-01 3.D-01 8.D-05 2.D-12  155C  0   0
  9 1.D+09 -1.785D+02 1.D+00 -6.936D+00 3.D-01 3.D-01 1.D-06 7.D-14  156C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 1.D+10 -1.785D+02 1.D+00 -6.936D+00 3.D-01 3.D-01 4.D-05 3.D-15  157C  0   0
 11 1.D+11 -1.785D+02 1.D+00 -6.936D+00 3.D-01 3.D-01 2.D+02 5.D-09  165P  0   0
 12 1.D+12 -1.785D+02 1.D+00 -6.936D+00 3.D-01 3.D-01 1.D-03 1.D-12  371P  0   0
 13 1.D+13 -1.785D+02 1.D+00 -6.936D+00 3.D-01 3.D-01 2.D+04 7.D-09  375P  0   0
 14 1.D+14 -1.785D+02 1.D+00 -6.936D+00 3.D-01 3.D-01 4.D+05 3.D-09  407P  0   0
 15 1.D+15 -1.785D+02 1.D+00 -6.936D+00 3.D-01 3.D-01 5.D+05 2.D-09  416P  0   0
 16 1.D+16 -1.785D+02 1.D+00 -6.936D+00 3.D-01 3.D-01 5.D+07 1.D-08  420P  0   0
 17 1.D+17 -1.785D+02 1.D+00 -6.936D+00 3.D-01 3.D-01 2.D+06 5.D-13  434P  0   0
 18 1.D+18 -1.785D+02 1.D+00 -6.936D+00 3.D-01 3.D-01 2.D+09 4.D-09  438P  0   0
 19 1.D+19 -1.785D+02 1.D+00 -6.936D+00 3.D-01 3.D-01 6.D+09 2.D-09  445P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 1.D+20 -1.785D+02 1.D+00 -6.936D+00 3.D-01 3.D-01 2.D+11 4.D-09  476P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.09

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   1522
 Subroutine evalg    (coded=T):    728
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  34457 (  1722 calls per constraint in average)
 Subroutine evaljac  (coded=T):   8181 (   409 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    474
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 84
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 5.6D-02
 Smallest constraints scale factor : 1.4D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -5.298D+01 3.D+00 -2.992D+00 1.D+00 1.D+00 9.D-01 1.D+00    0   0   0
  1 9.D+00 -3.292D+02 1.D+00 -1.859D+01 1.D+00 1.D+00 1.D+00 4.D-01   10C  0   0
  2 1.D+02 -1.620D+02 1.D+00 -9.149D+00 1.D+00 1.D+00 2.D-05 8.D-03   24C  0   0
  3 1.D+03 -1.622D+02 1.D+00 -9.162D+00 1.D+00 1.D+00 2.D-05 6.D-06   32C  0   0
  4 1.D+04 -1.622D+02 1.D+00 -9.162D+00 1.D+00 1.D+00 2.D-06 2.D-07   45C  0   0
  5 1.D+05 -1.622D+02 1.D+00 -9.162D+00 1.D+00 1.D+00 1.D-04 2.D-10   52C  0   0
  6 1.D+06 -1.622D+02 1.D+00 -9.162D+00 1.D+00 1.D+00 5.D-05 2.D-10   53C  0   0
  7 1.D+07 -1.622D+02 1.D+00 -9.162D+00 1.D+00 1.D+00 4.D-05 5.D-12   54C  0   0
  8 1.D+08 -1.622D+02 1.D+00 -9.162D+00 1.D+00 1.D+00 5.D-05 5.D-13   55C  0   0
  9 1.D+09 -1.622D+02 1.D+00 -9.162D+00 1.D+00 1.D+00 5.D-06 4.D-14   56C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 1.D+10 -1.622D+02 1.D+00 -9.162D+00 1.D+00 1.D+00 9.D-06 8.D-16  156C  0   0
 11 1.D+11 -1.622D+02 1.D+00 -9.162D+00 1.D+00 1.D+00 9.D-05 8.D-16  156C  0   0
 12 1.D+12 -1.622D+02 1.D+00 -9.162D+00 1.D+00 1.D+00 9.D-05 1.D-16  273C  0   0
 13 1.D+13 -1.622D+02 1.D+00 -9.162D+00 1.D+00 1.D+00 9.D-05 0.D+00  282C  0   0
 14 1.D+14 -1.622D+02 1.D+00 -9.162D+00 1.D+00 1.D+00 9.D-05 0.D+00  282C  0   0
 15 1.D+15 -1.622D+02 1.D+00 -9.162D+00 1.D+00 1.D+00 9.D-05 0.D+00  282C  0   0
 16 1.D+16 -1.622D+02 1.D+00 -9.162D+00 1.D+00 1.D+00 9.D-05 0.D+00  282C  0   0
 17 1.D+17 -1.622D+02 1.D+00 -9.162D+00 1.D+00 1.D+00 9.D-05 0.D+00  282C  0   0
 18 1.D+18 -1.622D+02 1.D+00 -9.162D+00 1.D+00 1.D+00 9.D-05 0.D+00  282C  0   0
 19 1.D+19 -1.622D+02 1.D+00 -9.162D+00 1.D+00 1.D+00 9.D-05 0.D+00  282C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 1.D+20 -1.622D+02 1.D+00 -9.162D+00 1.D+00 1.D+00 9.D-05 0.D+00  282C  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.06

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):    914
 Subroutine evalg    (coded=T):    500
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  21600 (  1080 calls per constraint in average)
 Subroutine evaljac  (coded=T):   5469 (   273 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    281
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 85
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 2.8D-02
 Smallest constraints scale factor : 7.5D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -1.799D+02 4.D+00 -4.971D+00 4.D+00 4.D+00 8.D-01 3.D+00    0   0   0
  1 5.D+00 -3.902D+02 1.D+00 -1.078D+01 1.D+00 1.D+00 2.D+00 5.D-01   10C  0   0
  2 7.D+01 -2.517D+02 1.D+00 -6.957D+00 1.D+00 1.D+00 5.D-06 9.D-03   99C  0   0
  3 7.D+02 -2.494D+02 1.D+00 -6.893D+00 1.D+00 1.D+00 8.D-06 4.D-05  108C  0   0
  4 7.D+03 -2.494D+02 1.D+00 -6.893D+00 1.D+00 1.D+00 1.D-04 3.D-09  110C  0   0
  5 7.D+04 -2.494D+02 1.D+00 -6.893D+00 1.D+00 1.D+00 1.D-04 2.D-09  112C  0   0
  6 7.D+05 -2.494D+02 1.D+00 -6.893D+00 1.D+00 1.D+00 5.D-05 9.D-11  116C  0   0
  7 7.D+06 -2.494D+02 1.D+00 -6.893D+00 1.D+00 1.D+00 6.D-07 2.D-11  117C  0   0
  8 7.D+07 -2.494D+02 1.D+00 -6.893D+00 1.D+00 1.D+00 6.D-07 7.D-16  118C  0   0
  9 7.D+08 -2.494D+02 1.D+00 -6.893D+00 1.D+00 1.D+00 3.D-06 7.D-16  118C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 7.D+09 -2.494D+02 1.D+00 -6.893D+00 1.D+00 1.D+00 3.D-05 7.D-16  118C  0   0
 11 7.D+10 -2.494D+02 1.D+00 -6.893D+00 1.D+00 1.D+00 2.D-04 3.D-15  124P  0   0
 12 7.D+11 -2.494D+02 1.D+00 -6.893D+00 1.D+00 1.D+00 8.D+03 4.D-08  130P  0   0
 13 7.D+12 -2.494D+02 1.D+00 -6.893D+00 1.D+00 1.D+00 3.D+04 7.D-09  173P  0   0
 14 7.D+13 -2.494D+02 1.D+00 -6.893D+00 1.D+00 1.D+00 2.D+05 1.D-08  200P  0   0
 15 7.D+14 -2.494D+02 1.D+00 -6.893D+00 1.D+00 1.D+00 3.D+06 5.D-09  205P  0   0
 16 7.D+15 -2.494D+02 1.D+00 -6.893D+00 1.D+00 1.D+00 6.D+05 8.D-10  352P  0   0
 17 7.D+16 -2.494D+02 1.D+00 -6.893D+00 1.D+00 1.D+00 4.D+08 1.D-08  357P  0   0
 18 7.D+17 -2.494D+02 1.D+00 -6.893D+00 1.D+00 1.D+00 2.D+08 5.D-10  361P  0   0
 19 7.D+18 -2.494D+02 1.D+00 -6.893D+00 1.D+00 1.D+00 6.D+10 3.D-08  365P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 7.D+19 -2.494D+02 1.D+00 -6.893D+00 1.D+00 1.D+00 3.D+11 8.D-09  411P  0   0
 21 7.D+20 -2.494D+02 1.D+00 -6.893D+00 1.D+00 1.D+00 2.D+12 9.D-09  416P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.13

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   2227
 Subroutine evalg    (coded=T):    536
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  45904 (  2295 calls per constraint in average)
 Subroutine evaljac  (coded=T):   5993 (   299 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    413
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 86
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 2.4D-02
 Smallest constraints scale factor : 6.5D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -1.427D+02 3.D+00 -3.389D+00 2.D+00 2.D+00 8.D-01 2.D+00    0   0   0
  1 8.D+00 -3.652D+02 1.D+00 -8.675D+00 1.D+00 1.D+00 6.D-01 2.D-01   10C  0   0
  2 7.D+01 -2.788D+02 1.D+00 -6.624D+00 1.D+00 1.D+00 3.D-08 1.D-02   37C  0   0
  3 7.D+02 -2.789D+02 1.D+00 -6.625D+00 1.D+00 1.D+00 2.D-05 6.D-05   45C  0   0
  4 7.D+03 -2.789D+02 1.D+00 -6.625D+00 1.D+00 1.D+00 7.D-10 7.D-08   48C  0   0
  5 7.D+04 -2.789D+02 1.D+00 -6.625D+00 1.D+00 1.D+00 2.D-05 5.D-10   49C  0   0
  6 7.D+05 -2.789D+02 1.D+00 -6.625D+00 1.D+00 1.D+00 1.D-05 3.D-11   50C  0   0
  7 7.D+06 -2.789D+02 1.D+00 -6.625D+00 1.D+00 1.D+00 2.D-05 3.D-12   51C  0   0
  8 7.D+07 -2.789D+02 1.D+00 -6.625D+00 1.D+00 1.D+00 3.D-05 8.D-13   52C  0   0
  9 7.D+08 -2.789D+02 1.D+00 -6.625D+00 1.D+00 1.D+00 2.D-05 4.D-14   53C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 7.D+09 -2.789D+02 1.D+00 -6.625D+00 1.D+00 1.D+00 1.D-05 3.D-15   54C  0   0
 11 7.D+10 -2.789D+02 1.D+00 -6.625D+00 1.D+00 1.D+00 3.D-05 4.D-16   55C  0   0
 12 7.D+11 -2.789D+02 1.D+00 -6.625D+00 1.D+00 1.D+00 8.D-05 1.D-16   58C  0   0
 13 7.D+12 -2.789D+02 1.D+00 -6.625D+00 1.D+00 1.D+00 5.D-03 3.D-16   61P  0   0
 14 7.D+13 -2.789D+02 1.D+00 -6.625D+00 1.D+00 1.D+00 6.D-02 5.D-17   66P  0   0
 15 7.D+14 -2.789D+02 1.D+00 -6.625D+00 1.D+00 1.D+00 9.D+06 4.D-08   70P  0   0
 16 7.D+15 -2.789D+02 1.D+00 -6.625D+00 1.D+00 1.D+00 3.D+07 9.D-09  193P  0   0
 17 7.D+16 -2.789D+02 1.D+00 -6.625D+00 1.D+00 1.D+00 9.D+08 4.D-08  198P  0   0
 18 7.D+17 -2.789D+02 1.D+00 -6.625D+00 1.D+00 1.D+00 1.D+09 2.D-09  207P  0   0
 19 7.D+18 -2.789D+02 1.D+00 -6.625D+00 1.D+00 1.D+00 2.D+10 1.D-08  219P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 7.D+19 -2.789D+02 1.D+00 -6.625D+00 1.D+00 1.D+00 2.D+11 9.D-09  271P  0   0
 21 7.D+20 -2.789D+02 1.D+00 -6.625D+00 1.D+00 1.D+00 2.D+12 3.D-09  283P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.08

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   1323
 Subroutine evalg    (coded=T):    364
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  27041 (  1352 calls per constraint in average)
 Subroutine evaljac  (coded=T):   4280 (   214 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    282
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 87
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 5.5D-02
 Smallest constraints scale factor : 1.5D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -1.925D+01 4.D+00 -1.056D+00 2.D+00 2.D+00 5.D-01 3.D+00    0   0   0
  1 1.D+00 -1.498D+03 4.D+00 -8.221D+01 4.D+00 4.D+00 2.D+00 5.D+00   10C  0   0
  2 3.D+01 -3.128D+02 1.D+00 -1.716D+01 1.D+00 1.D+00 3.D-08 6.D-02   29C  0   0
  3 3.D+01 -3.028D+02 1.D+00 -1.662D+01 1.D+00 1.D+00 2.D-07 6.D-02   37C  0   0
  4 3.D+02 -2.979D+02 1.D+00 -1.634D+01 1.D+00 1.D+00 1.D-05 2.D-03   47C  0   0
  5 3.D+03 -2.978D+02 1.D+00 -1.634D+01 1.D+00 1.D+00 1.D-09 2.D-05   52C  0   0
  6 3.D+04 -2.978D+02 1.D+00 -1.634D+01 1.D+00 1.D+00 1.D-09 1.D-08   55C  0   0
  7 3.D+05 -2.978D+02 1.D+00 -1.634D+01 1.D+00 1.D+00 4.D-05 1.D-10   56C  0   0
  8 3.D+06 -2.978D+02 1.D+00 -1.634D+01 1.D+00 1.D+00 2.D-05 1.D-11   57C  0   0
  9 3.D+07 -2.978D+02 1.D+00 -1.634D+01 1.D+00 1.D+00 3.D-05 9.D-13   58C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 3.D+08 -2.978D+02 1.D+00 -1.634D+01 1.D+00 1.D+00 2.D-05 2.D-13   59C  0   0
 11 3.D+09 -2.978D+02 1.D+00 -1.634D+01 1.D+00 1.D+00 4.D-05 7.D-15   60C  0   0
 12 3.D+10 -2.978D+02 1.D+00 -1.634D+01 1.D+00 1.D+00 3.D-05 1.D-15   61C  0   0
 13 3.D+11 -2.978D+02 1.D+00 -1.634D+01 1.D+00 1.D+00 6.D-05 2.D-16   66C  0   0
 14 3.D+12 -2.978D+02 1.D+00 -1.634D+01 1.D+00 1.D+00 4.D-03 0.D+00   72P  0   0
 15 3.D+13 -2.978D+02 1.D+00 -1.634D+01 1.D+00 1.D+00 3.D-02 1.D-15   76P  0   0
 16 3.D+14 -2.978D+02 1.D+00 -1.634D+01 1.D+00 1.D+00 5.D+05 2.D-09  289P  0   0
 17 3.D+15 -2.978D+02 1.D+00 -1.634D+01 1.D+00 1.D+00 4.D+07 1.D-08  296P  0   0
 18 3.D+16 -2.978D+02 1.D+00 -1.634D+01 1.D+00 1.D+00 4.D+08 1.D-08  332P  0   0
 19 3.D+17 -2.978D+02 1.D+00 -1.634D+01 1.D+00 1.D+00 3.D+08 8.D-10  359P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 3.D+18 -2.978D+02 1.D+00 -1.634D+01 1.D+00 1.D+00 4.D+09 1.D-09  380P  0   0
 21 3.D+19 -2.978D+02 1.D+00 -1.634D+01 1.D+00 1.D+00 2.D+11 5.D-09  397P  0   0
 22 3.D+20 -2.978D+02 1.D+00 -1.634D+01 1.D+00 1.D+00 3.D+11 7.D-10  522P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.10

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   2416
 Subroutine evalg    (coded=T):    599
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  48826 (  2441 calls per constraint in average)
 Subroutine evaljac  (coded=T):   7259 (   362 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    520
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 88
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 2.7D-02
 Smallest constraints scale factor : 8.8D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -8.022D+01 4.D+00 -2.131D+00 3.D+00 3.D+00 6.D-01 4.D+00    0   0   0
  1 2.D+00 -7.378D+02 4.D+00 -1.960D+01 2.D+00 2.D+00 1.D+00 1.D+00   10C  0   0
  2 4.D+01 -2.766D+02 1.D+00 -7.348D+00 1.D+00 1.D+00 6.D-05 2.D-02   24C  0   0
  3 4.D+02 -2.722D+02 1.D+00 -7.229D+00 1.D+00 1.D+00 2.D-09 8.D-05   30C  0   0
  4 4.D+03 -2.722D+02 1.D+00 -7.229D+00 1.D+00 1.D+00 1.D-07 2.D-07   33C  0   0
  5 4.D+04 -2.722D+02 1.D+00 -7.229D+00 1.D+00 1.D+00 3.D-07 6.D-11   35C  0   0
  6 4.D+05 -2.722D+02 1.D+00 -7.229D+00 1.D+00 1.D+00 2.D-05 6.D-11   35C  0   0
  7 4.D+06 -2.722D+02 1.D+00 -7.229D+00 1.D+00 1.D+00 2.D-05 6.D-12   36C  0   0
  8 4.D+07 -2.722D+02 1.D+00 -7.229D+00 1.D+00 1.D+00 1.D-05 7.D-13   37C  0   0
  9 4.D+08 -2.722D+02 1.D+00 -7.229D+00 1.D+00 1.D+00 7.D-07 3.D-14   38C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 4.D+09 -2.722D+02 1.D+00 -7.229D+00 1.D+00 1.D+00 1.D-04 3.D-14   38C  0   0
 11 4.D+10 -2.722D+02 1.D+00 -7.229D+00 1.D+00 1.D+00 2.D-05 5.D-15   39C  0   0
 12 4.D+11 -2.722D+02 1.D+00 -7.229D+00 1.D+00 1.D+00 4.D-05 8.D-17   43C  0   0
 13 4.D+12 -2.722D+02 1.D+00 -7.229D+00 1.D+00 1.D+00 6.D-04 1.D-16   46P  0   0
 14 4.D+13 -2.722D+02 1.D+00 -7.229D+00 1.D+00 1.D+00 7.D-03 2.D-16   52P  0   0
 15 4.D+14 -2.722D+02 1.D+00 -7.229D+00 1.D+00 1.D+00 5.D-02 1.D-16   56P  0   0
 16 4.D+15 -2.722D+02 1.D+00 -7.229D+00 1.D+00 1.D+00 7.D+07 2.D-08   61P  0   0
 17 4.D+16 -2.722D+02 1.D+00 -7.229D+00 1.D+00 1.D+00 7.D+08 2.D-08   66P  0   0
 18 4.D+17 -2.722D+02 1.D+00 -7.229D+00 1.D+00 1.D+00 1.D+10 2.D-08   72P  0   0
 19 4.D+18 -2.722D+02 1.D+00 -7.229D+00 1.D+00 1.D+00 1.D+11 2.D-08   79P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 4.D+19 -2.722D+02 1.D+00 -7.229D+00 1.D+00 1.D+00 1.D+12 2.D-08   85P  0   0
 21 4.D+20 -2.722D+02 1.D+00 -7.229D+00 1.D+00 1.D+00 7.D+12 2.D-08   90P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.02

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):    279
 Subroutine evalg    (coded=T):    159
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):   5931 (   296 calls per constraint in average)
 Subroutine evaljac  (coded=T):   2041 (   102 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):     90
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 89
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 4.8D-02
 Smallest constraints scale factor : 1.4D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -7.822D+01 4.D+00 -3.781D+00 4.D+00 4.D+00 1.D+00 3.D+00    0   0   0
  1 2.D+00 -7.165D+02 2.D+00 -3.463D+01 2.D+00 2.D+00 1.D+00 2.D+00   10C  0   0
  2 7.D+01 -2.449D+02 1.D+00 -1.184D+01 8.D-01 8.D-01 2.D-08 3.D-02   34C  0   0
  3 7.D+01 -2.378D+02 1.D+00 -1.150D+01 8.D-01 8.D-01 4.D-05 1.D-03   37C  0   0
  4 7.D+02 -2.379D+02 1.D+00 -1.150D+01 8.D-01 8.D-01 2.D-05 3.D-05   40C  0   0
  5 7.D+03 -2.379D+02 1.D+00 -1.150D+01 8.D-01 8.D-01 4.D-11 7.D-08   42C  0   0
  6 7.D+04 -2.379D+02 1.D+00 -1.150D+01 8.D-01 8.D-01 4.D-10 2.D-11   44C  0   0
  7 7.D+05 -2.379D+02 1.D+00 -1.150D+01 8.D-01 8.D-01 9.D-06 2.D-11   44C  0   0
  8 7.D+06 -2.379D+02 1.D+00 -1.150D+01 8.D-01 8.D-01 9.D-05 2.D-11   44C  0   0
  9 7.D+07 -2.379D+02 1.D+00 -1.150D+01 8.D-01 8.D-01 1.D-05 2.D-12   45C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 7.D+08 -2.379D+02 1.D+00 -1.150D+01 8.D-01 8.D-01 2.D-05 3.D-14   46C  0   0
 11 7.D+09 -2.379D+02 1.D+00 -1.150D+01 8.D-01 8.D-01 3.D-06 2.D-15   47C  0   0
 12 7.D+10 -2.379D+02 1.D+00 -1.150D+01 8.D-01 8.D-01 5.D-05 6.D-16   48C  0   0
 13 7.D+11 -2.379D+02 1.D+00 -1.150D+01 8.D-01 8.D-01 3.D-03 6.D-17   51P  0   0
 14 7.D+12 -2.379D+02 1.D+00 -1.150D+01 8.D-01 8.D-01 1.D+03 1.D-10  121P  0   0
 15 7.D+13 -2.379D+02 1.D+00 -1.150D+01 8.D-01 8.D-01 3.D+04 5.D-10  191P  0   0
 16 7.D+14 -2.379D+02 1.D+00 -1.150D+01 8.D-01 8.D-01 8.D+06 1.D-08  195P  0   0
 17 7.D+15 -2.379D+02 1.D+00 -1.150D+01 8.D-01 8.D-01 1.D+06 2.D-10  242P  0   0
 18 7.D+16 -2.379D+02 1.D+00 -1.150D+01 8.D-01 8.D-01 7.D+08 1.D-08  256P  0   0
 19 7.D+17 -2.379D+02 1.D+00 -1.150D+01 8.D-01 8.D-01 2.D+08 5.D-13  291P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 7.D+18 -2.379D+02 1.D+00 -1.150D+01 8.D-01 8.D-01 2.D+11 2.D-08  296P  0   0
 21 7.D+19 -2.379D+02 1.D+00 -1.150D+01 8.D-01 8.D-01 9.D+11 1.D-08  395P  0   0
 22 7.D+20 -2.379D+02 1.D+00 -1.150D+01 8.D-01 8.D-01 8.D+12 1.D-08  429P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.09

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   2014
 Subroutine evalg    (coded=T):    512
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  40820 (  2041 calls per constraint in average)
 Subroutine evaljac  (coded=T):   5516 (   275 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    433
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 90
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 5.0D-02
 Smallest constraints scale factor : 1.2D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -6.088D+01 3.D+00 -3.062D+00 3.D+00 3.D+00 1.D+00 3.D+00    0   0   0
  1 4.D+00 -4.994D+02 1.D+00 -2.512D+01 1.D+00 1.D+00 1.D+00 8.D-01   10C  0   0
  2 9.D+01 -2.044D+02 1.D+00 -1.028D+01 1.D+00 1.D+00 2.D-08 2.D-02   24C  0   0
  3 9.D+02 -2.000D+02 1.D+00 -1.006D+01 1.D+00 1.D+00 5.D-07 1.D-05   31C  0   0
  4 9.D+03 -2.000D+02 1.D+00 -1.006D+01 1.D+00 1.D+00 1.D-08 4.D-10   33C  0   0
  5 9.D+04 -2.000D+02 1.D+00 -1.006D+01 1.D+00 1.D+00 4.D-05 4.D-10   33C  0   0
  6 9.D+05 -2.000D+02 1.D+00 -1.006D+01 1.D+00 1.D+00 2.D-05 2.D-11   34C  0   0
  7 9.D+06 -2.000D+02 1.D+00 -1.006D+01 1.D+00 1.D+00 5.D-05 5.D-12   35C  0   0
  8 9.D+07 -2.000D+02 1.D+00 -1.006D+01 1.D+00 1.D+00 2.D-05 5.D-13   36C  0   0
  9 9.D+08 -2.000D+02 1.D+00 -1.006D+01 1.D+00 1.D+00 1.D-06 5.D-14   38C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 9.D+09 -2.000D+02 1.D+00 -1.006D+01 1.D+00 1.D+00 1.D-06 0.D+00   40C  0   0
 11 9.D+10 -2.000D+02 1.D+00 -1.006D+01 1.D+00 1.D+00 1.D-06 0.D+00   40C  0   0
 12 9.D+11 -2.000D+02 1.D+00 -1.006D+01 1.D+00 1.D+00 1.D-06 0.D+00   40C  0   0
 13 9.D+12 -2.000D+02 1.D+00 -1.006D+01 1.D+00 1.D+00 1.D-06 0.D+00   40C  0   0
 14 9.D+13 -2.000D+02 1.D+00 -1.006D+01 1.D+00 1.D+00 1.D-06 0.D+00   40C  0   0
 15 9.D+14 -2.000D+02 1.D+00 -1.006D+01 1.D+00 1.D+00 1.D-06 0.D+00   40C  0   0
 16 9.D+15 -2.000D+02 1.D+00 -1.006D+01 1.D+00 1.D+00 1.D-06 0.D+00   40C  0   0
 17 9.D+16 -2.000D+02 1.D+00 -1.006D+01 1.D+00 1.D+00 1.D-06 0.D+00   40C  0   0
 18 9.D+17 -2.000D+02 1.D+00 -1.006D+01 1.D+00 1.D+00 1.D-06 0.D+00   40C  0   0
 19 9.D+18 -2.000D+02 1.D+00 -1.006D+01 1.D+00 1.D+00 1.D-06 0.D+00   40C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 9.D+19 -2.000D+02 1.D+00 -1.006D+01 1.D+00 1.D+00 1.D-06 0.D+00   40C  0   0
 21 9.D+20 -2.000D+02 1.D+00 -1.006D+01 1.D+00 1.D+00 1.D-06 0.D+00   40C  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.02

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):    117
 Subroutine evalg    (coded=T):    112
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):   2710 (   135 calls per constraint in average)
 Subroutine evaljac  (coded=T):   1201 (    60 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):     40
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 91
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 3.9D-02
 Smallest constraints scale factor : 9.4D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -7.338D+01 3.D+00 -2.834D+00 1.D+00 1.D+00 1.D+00 9.D-01    0   0   0
  1 1.D+01 -1.724D+02 1.D+00 -6.658D+00 4.D-01 4.D-01 1.D+00 2.D-01   10C  0   0
  2 7.D+01 -1.403D+02 1.D+00 -5.418D+00 4.D-01 4.D-01 5.D-07 2.D-02   34C  0   0
  3 7.D+02 -1.357D+02 1.D+00 -5.242D+00 4.D-01 4.D-01 6.D-05 4.D-05   54C  0   0
  4 7.D+03 -1.357D+02 1.D+00 -5.242D+00 4.D-01 4.D-01 5.D-05 2.D-08   56C  0   0
  5 7.D+04 -1.357D+02 1.D+00 -5.242D+00 4.D-01 4.D-01 6.D-05 9.D-10   57C  0   0
  6 7.D+05 -1.357D+02 1.D+00 -5.242D+00 4.D-01 4.D-01 2.D-05 6.D-11   58C  0   0
  7 7.D+06 -1.357D+02 1.D+00 -5.242D+00 4.D-01 4.D-01 2.D-05 4.D-12   59C  0   0
  8 7.D+07 -1.357D+02 1.D+00 -5.242D+00 4.D-01 4.D-01 8.D-06 4.D-13   60C  0   0
  9 7.D+08 -1.357D+02 1.D+00 -5.242D+00 4.D-01 4.D-01 1.D-05 2.D-14   61C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 7.D+09 -1.357D+02 1.D+00 -5.242D+00 4.D-01 4.D-01 2.D-05 2.D-15   62C  0   0
 11 7.D+10 -1.357D+02 1.D+00 -5.242D+00 4.D-01 4.D-01 1.D-05 4.D-16   63C  0   0
 12 7.D+11 -1.357D+02 1.D+00 -5.242D+00 4.D-01 4.D-01 6.D-04 8.D-16   71P  0   0
 13 7.D+12 -1.357D+02 1.D+00 -5.242D+00 4.D-01 4.D-01 3.D+03 2.D-09   77P  0   0
 14 7.D+13 -1.357D+02 1.D+00 -5.242D+00 4.D-01 4.D-01 2.D+05 8.D-09   89P  0   0
 15 7.D+14 -1.357D+02 1.D+00 -5.242D+00 4.D-01 4.D-01 1.D+06 5.D-09   94P  0   0
 16 7.D+15 -1.357D+02 1.D+00 -5.242D+00 4.D-01 4.D-01 2.D+07 1.D-08   98P  0   0
 17 7.D+16 -1.357D+02 1.D+00 -5.242D+00 4.D-01 4.D-01 2.D+05 2.D-12  120P  0   0
 18 7.D+17 -1.357D+02 1.D+00 -5.242D+00 4.D-01 4.D-01 1.D+09 7.D-09  125P  0   0
 19 7.D+18 -1.357D+02 1.D+00 -5.242D+00 4.D-01 4.D-01 6.D+06 1.D-12  137P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 7.D+19 -1.357D+02 1.D+00 -5.242D+00 4.D-01 4.D-01 7.D+10 4.D-09  141P  0   0
 21 7.D+20 -1.357D+02 1.D+00 -5.242D+00 4.D-01 4.D-01 9.D+11 5.D-09  216P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.05

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   1036
 Subroutine evalg    (coded=T):    295
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  21227 (  1061 calls per constraint in average)
 Subroutine evaljac  (coded=T):   2983 (   149 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    216
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 92
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 2.5D-02
 Smallest constraints scale factor : 9.0D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -9.215D+01 3.D+00 -2.347D+00 3.D+00 3.D+00 5.D-01 3.D+00    0   0   0
  1 4.D+00 -2.593D+02 1.D+00 -6.604D+00 1.D+00 1.D+00 1.D+00 5.D-01   10C  0   0
  2 7.D+01 -1.643D+02 1.D+00 -4.184D+00 1.D+00 1.D+00 2.D-05 3.D-02   23C  0   0
  3 7.D+02 -1.641D+02 1.D+00 -4.181D+00 1.D+00 1.D+00 3.D-08 4.D-05   26C  0   0
  4 7.D+03 -1.641D+02 1.D+00 -4.181D+00 1.D+00 1.D+00 7.D-06 1.D-07   28C  0   0
  5 7.D+04 -1.641D+02 1.D+00 -4.181D+00 1.D+00 1.D+00 3.D-10 2.D-09   30C  0   0
  6 7.D+05 -1.585D+02 1.D+00 -4.037D+00 1.D+00 1.D+00 1.D+00 5.D-03 1030M  0   0
  7 7.D+06 -1.620D+02 1.D+00 -4.125D+00 1.D+00 1.D+00 5.D-01 1.D-07 2030M  0   0
  8 7.D+07 -1.625D+02 1.D+00 -4.140D+00 1.D+00 1.D+00 4.D-01 9.D-09 3030M  0   0
  9 7.D+08 -1.625D+02 1.D+00 -4.140D+00 1.D+00 1.D+00 3.D-01 6.D-10 4030M  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 7.D+09 -1.626D+02 1.D+00 -4.142D+00 1.D+00 1.D+00 4.D-01 8.D-11 5030M  0   0
 11 7.D+10 -1.626D+02 1.D+00 -4.142D+00 1.D+00 1.D+00 4.D-01 6.D-12 6030M  0   0
 12 7.D+11 -1.626D+02 1.D+00 -4.142D+00 1.D+00 1.D+00 6.D+02 1.D-09 6034P  0   0
 13 7.D+12 -1.626D+02 1.D+00 -4.142D+00 1.D+00 1.D+00 4.D+04 2.D-08 6038P  0   0
 14 7.D+13 -1.626D+02 1.D+00 -4.142D+00 1.D+00 1.D+00 1.D+04 3.D-10 6042P  0   0
 15 7.D+14 -1.626D+02 1.D+00 -4.142D+00 1.D+00 1.D+00 3.D+06 2.D-08 6046P  0   0
 16 7.D+15 -1.626D+02 1.D+00 -4.142D+00 1.D+00 1.D+00 2.D+07 8.D-09 6103P  0   0
 17 7.D+16 -1.626D+02 1.D+00 -4.142D+00 1.D+00 1.D+00 2.D+08 1.D-08 6110P  0   0
 18 7.D+17 -1.626D+02 1.D+00 -4.142D+00 1.D+00 1.D+00 2.D+09 1.D-08 6140P  0   0
 19 7.D+18 -1.626D+02 1.D+00 -4.142D+00 1.D+00 1.D+00 1.D+10 7.D-09 6155P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 7.D+19 -1.626D+02 1.D+00 -4.142D+00 1.D+00 1.D+00 3.D+11 2.D-08 6182P  0   0
 21 7.D+20 -1.626D+02 1.D+00 -4.142D+00 1.D+00 1.D+00 1.D+12 6.D-09 6199P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     1.02

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):  19056
 Subroutine evalg    (coded=T):  10912
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T): 474274 ( 23713 calls per constraint in average)
 Subroutine evaljac  (coded=T): 111287 (  5564 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):   6195
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 93
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 3.9D-02
 Smallest constraints scale factor : 1.0D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -6.947D+01 3.D+00 -2.698D+00 2.D+00 2.D+00 9.D-01 2.D+00    0   0   0
  1 6.D+00 -3.840D+02 1.D+00 -1.491D+01 1.D+00 1.D+00 4.D+00 7.D-01   10C  0   0
  2 1.D+02 -2.522D+02 1.D+00 -9.793D+00 1.D+00 1.D+00 2.D-06 8.D-03   91C  0   0
  3 1.D+03 -2.494D+02 1.D+00 -9.684D+00 1.D+00 1.D+00 7.D-05 1.D-05  110C  0   0
  4 1.D+04 -2.494D+02 1.D+00 -9.684D+00 1.D+00 1.D+00 4.D-06 4.D-09  112C  0   0
  5 1.D+05 -2.494D+02 1.D+00 -9.684D+00 1.D+00 1.D+00 5.D-05 4.D-10  113C  0   0
  6 1.D+06 -2.494D+02 1.D+00 -9.684D+00 1.D+00 1.D+00 4.D-06 3.D-11  114C  0   0
  7 1.D+07 -2.494D+02 1.D+00 -9.684D+00 1.D+00 1.D+00 5.D-06 6.D-13  115C  0   0
  8 1.D+08 -2.494D+02 1.D+00 -9.684D+00 1.D+00 1.D+00 8.D-05 6.D-13  115C  0   0
  9 1.D+09 -2.494D+02 1.D+00 -9.684D+00 1.D+00 1.D+00 3.D-06 4.D-14  116C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 1.D+10 -2.494D+02 1.D+00 -9.684D+00 1.D+00 1.D+00 5.D-05 2.D-15  117C  0   0
 11 1.D+11 -2.494D+02 1.D+00 -9.684D+00 1.D+00 1.D+00 2.D-04 6.D-16  125P  0   0
 12 1.D+12 -2.494D+02 1.D+00 -9.684D+00 1.D+00 1.D+00 1.D-03 6.D-16  129P  0   0
 13 1.D+13 -1.724D+02 1.D+00 -6.695D+00 4.D-01 4.D-01 8.D+03 2.D-09  184P  0   0
 14 1.D+13 -1.735D+02 1.D+00 -6.737D+00 4.D-01 4.D-01 8.D+04 6.D-09  188P  0   0
 15 1.D+14 -1.735D+02 1.D+00 -6.737D+00 4.D-01 4.D-01 9.D-01 6.D-10 1188M  0   0
 16 1.D+15 -1.735D+02 1.D+00 -6.737D+00 4.D-01 4.D-01 1.D+06 4.D-09 1192P  0   0
 17 1.D+16 -1.735D+02 1.D+00 -6.737D+00 4.D-01 4.D-01 6.D+06 4.D-10 1197P  0   0
 18 1.D+17 -1.735D+02 1.D+00 -6.737D+00 4.D-01 4.D-01 1.D+08 4.D-09 1201P  0   0
 19 1.D+18 -1.735D+02 1.D+00 -6.737D+00 4.D-01 4.D-01 5.D+09 1.D-08 1206P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 1.D+19 -1.735D+02 1.D+00 -6.737D+00 4.D-01 4.D-01 2.D+07 8.D-13 1210P  0   0
 21 1.D+20 -1.735D+02 1.D+00 -6.737D+00 4.D-01 4.D-01 3.D+11 8.D-09 1215P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.22

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   3975
 Subroutine evalg    (coded=T):   2290
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  99972 (  4998 calls per constraint in average)
 Subroutine evaljac  (coded=T):  21135 (  1056 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):   1212
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 94
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 2.6D-02
 Smallest constraints scale factor : 7.7D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -8.062D+01 4.D+00 -2.131D+00 3.D+00 3.D+00 6.D-01 2.D+00    0   0   0
  1 3.D+00 -4.669D+02 1.D+00 -1.234D+01 9.D-01 9.D-01 1.D+00 6.D-01   10C  0   0
  2 1.D+02 -2.302D+02 1.D+00 -6.082D+00 4.D-01 4.D-01 3.D-05 8.D-03   34C  0   0
  3 1.D+02 -2.280D+02 1.D+00 -6.026D+00 4.D-01 4.D-01 2.D-06 6.D-05   37C  0   0
  4 1.D+03 -2.281D+02 1.D+00 -6.027D+00 4.D-01 4.D-01 2.D-05 2.D-07   39C  0   0
  5 1.D+04 -2.281D+02 1.D+00 -6.027D+00 4.D-01 4.D-01 5.D-05 9.D-09   40C  0   0
  6 1.D+05 -2.281D+02 1.D+00 -6.027D+00 4.D-01 4.D-01 4.D-05 7.D-10   41C  0   0
  7 1.D+06 -2.281D+02 1.D+00 -6.027D+00 4.D-01 4.D-01 6.D-05 7.D-11   42C  0   0
  8 1.D+07 -2.281D+02 1.D+00 -6.027D+00 4.D-01 4.D-01 3.D-05 5.D-12   43C  0   0
  9 1.D+08 -2.281D+02 1.D+00 -6.027D+00 4.D-01 4.D-01 6.D-06 4.D-13   44C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 1.D+09 -2.281D+02 1.D+00 -6.027D+00 4.D-01 4.D-01 2.D-05 2.D-14   45C  0   0
 11 1.D+10 -2.281D+02 1.D+00 -6.027D+00 4.D-01 4.D-01 2.D-05 2.D-15   48C  0   0
 12 1.D+11 -2.281D+02 1.D+00 -6.027D+00 4.D-01 4.D-01 4.D+02 1.D-08   55P  0   0
 13 1.D+12 -2.281D+02 1.D+00 -6.027D+00 4.D-01 4.D-01 4.D+03 1.D-08  431P  0   0
 14 1.D+13 -2.281D+02 1.D+00 -6.027D+00 4.D-01 4.D-01 1.D+04 3.D-09  506P  0   0
 15 1.D+14 -2.281D+02 1.D+00 -6.027D+00 4.D-01 4.D-01 6.D+04 1.D-09  655P  0   0
 16 1.D+15 -2.281D+02 1.D+00 -6.027D+00 4.D-01 4.D-01 7.D+04 6.D-11  694P  0   0
 17 1.D+16 -2.281D+02 1.D+00 -6.027D+00 4.D-01 4.D-01 4.D+02 1.D-11  942P  0   0
 18 1.D+17 -2.281D+02 1.D+00 -6.027D+00 4.D-01 4.D-01 1.D+08 4.D-09  946P  0   0
 19 1.D+18 -2.281D+02 1.D+00 -6.027D+00 4.D-01 4.D-01 8.D+07 7.D-11  985P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 1.D+19 -2.281D+02 1.D+00 -6.027D+00 4.D-01 4.D-01 8.D+08 7.D-11 1134P  0   0
 21 1.D+20 -2.281D+02 1.D+00 -6.027D+00 4.D-01 4.D-01 4.D+06 2.D-11 1333P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.37

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   6617
 Subroutine evalg    (coded=T):   1419
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T): 133037 (  6651 calls per constraint in average)
 Subroutine evaljac  (coded=T):  16015 (   800 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):   1330
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 95
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 3.6D-02
 Smallest constraints scale factor : 9.1D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -9.876D+01 3.D+00 -3.579D+00 2.D+00 2.D+00 1.D+00 8.D-01    0   0   0
  1 1.D+01 -1.781D+02 1.D+00 -6.455D+00 3.D-01 3.D-01 1.D+00 8.D-02   10C  0   0
  2 6.D+01 -1.370D+02 1.D+00 -4.964D+00 3.D-01 3.D-01 5.D-05 2.D-02   31C  0   0
  3 6.D+02 -1.357D+02 1.D+00 -4.919D+00 3.D-01 3.D-01 2.D-06 3.D-05   48C  0   0
  4 6.D+03 -1.357D+02 1.D+00 -4.919D+00 3.D-01 3.D-01 1.D-04 1.D-08   50C  0   0
  5 6.D+04 -1.357D+02 1.D+00 -4.919D+00 3.D-01 3.D-01 3.D-05 1.D-09   51C  0   0
  6 6.D+05 -1.357D+02 1.D+00 -4.919D+00 3.D-01 3.D-01 4.D-05 6.D-11   52C  0   0
  7 6.D+06 -1.357D+02 1.D+00 -4.919D+00 3.D-01 3.D-01 1.D-05 4.D-12   53C  0   0
  8 6.D+07 -1.357D+02 1.D+00 -4.919D+00 3.D-01 3.D-01 2.D-05 3.D-13   54C  0   0
  9 6.D+08 -1.357D+02 1.D+00 -4.919D+00 3.D-01 3.D-01 7.D-06 1.D-14   55C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 6.D+09 -1.357D+02 1.D+00 -4.919D+00 3.D-01 3.D-01 1.D-05 2.D-15   56C  0   0
 11 6.D+10 -1.357D+02 1.D+00 -4.919D+00 3.D-01 3.D-01 7.D-05 2.D-16   57C  0   0
 12 6.D+11 -1.357D+02 1.D+00 -4.919D+00 3.D-01 3.D-01 1.D+03 3.D-09   64P  0   0
 13 6.D+12 -1.357D+02 1.D+00 -4.919D+00 3.D-01 3.D-01 1.D+04 2.D-09  107P  0   0
 14 6.D+13 -1.357D+02 1.D+00 -4.919D+00 3.D-01 3.D-01 2.D+04 1.D-09  117P  0   0
 15 6.D+14 -1.357D+02 1.D+00 -4.919D+00 3.D-01 3.D-01 1.D+05 2.D-10  159P  0   0
 16 6.D+15 -1.357D+02 1.D+00 -4.919D+00 3.D-01 3.D-01 6.D+06 4.D-09  163P  0   0
 17 6.D+16 -1.357D+02 1.D+00 -4.919D+00 3.D-01 3.D-01 2.D+07 6.D-10  175P  0   0
 18 6.D+17 -1.357D+02 1.D+00 -4.919D+00 3.D-01 3.D-01 7.D+08 4.D-09  206P  0   0
 19 6.D+18 -1.357D+02 1.D+00 -4.919D+00 3.D-01 3.D-01 2.D+09 1.D-09  222P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 6.D+19 -1.357D+02 1.D+00 -4.919D+00 3.D-01 3.D-01 3.D+10 2.D-09  259P  0   0
 21 6.D+20 -1.357D+02 1.D+00 -4.919D+00 3.D-01 3.D-01 1.D+10 5.D-11  295P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.10

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   1485
 Subroutine evalg    (coded=T):    372
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  30171 (  1508 calls per constraint in average)
 Subroutine evaljac  (coded=T):   4122 (   206 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    294
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 96
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 2.8D-02
 Smallest constraints scale factor : 8.9D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -8.590D+01 4.D+00 -2.387D+00 3.D+00 3.D+00 8.D-01 2.D+00    0   0   0
  1 3.D+00 -5.288D+02 4.D+00 -1.469D+01 8.D-01 8.D-01 5.D-01 5.D-01   10C  0   0
  2 1.D+02 -2.309D+02 1.D+00 -6.415D+00 4.D-01 4.D-01 5.D-07 8.D-03   28C  0   0
  3 1.D+02 -2.293D+02 1.D+00 -6.372D+00 4.D-01 4.D-01 4.D-05 2.D-04   32C  0   0
  4 1.D+03 -2.293D+02 1.D+00 -6.373D+00 4.D-01 4.D-01 2.D-08 1.D-06   35C  0   0
  5 1.D+04 -2.293D+02 1.D+00 -6.373D+00 4.D-01 4.D-01 1.D-06 1.D-09   37C  0   0
  6 1.D+05 -2.293D+02 1.D+00 -6.373D+00 4.D-01 4.D-01 2.D-06 4.D-11   38C  0   0
  7 1.D+06 -2.293D+02 1.D+00 -6.373D+00 4.D-01 4.D-01 2.D-05 4.D-11   38C  0   0
  8 1.D+07 -2.293D+02 1.D+00 -6.373D+00 4.D-01 4.D-01 2.D-05 2.D-12   39C  0   0
  9 1.D+08 -2.293D+02 1.D+00 -6.373D+00 4.D-01 4.D-01 4.D-06 2.D-13   40C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 1.D+09 -2.293D+02 1.D+00 -6.373D+00 4.D-01 4.D-01 7.D-06 6.D-15   41C  0   0
 11 1.D+10 -2.293D+02 1.D+00 -6.373D+00 4.D-01 4.D-01 7.D-05 6.D-15   41C  0   0
 12 1.D+11 -2.293D+02 1.D+00 -6.373D+00 4.D-01 4.D-01 3.D-05 9.D-16   42C  0   0
 13 1.D+12 -2.293D+02 1.D+00 -6.373D+00 4.D-01 4.D-01 8.D-05 8.D-17   45C  0   0
 14 1.D+13 -2.293D+02 1.D+00 -6.373D+00 4.D-01 4.D-01 2.D-03 2.D-16   49P  0   0
 15 1.D+14 -2.293D+02 1.D+00 -6.373D+00 4.D-01 4.D-01 1.D-02 1.D-16   59P  0   0
 16 1.D+15 -2.293D+02 1.D+00 -6.373D+00 4.D-01 4.D-01 2.D+06 2.D-09   64P  0   0
 17 1.D+16 -2.293D+02 1.D+00 -6.373D+00 4.D-01 4.D-01 3.D+05 4.D-11  361P  0   0
 18 1.D+17 -2.293D+02 1.D+00 -6.373D+00 4.D-01 4.D-01 6.D+07 5.D-10  365P  0   0
 19 1.D+18 -2.293D+02 1.D+00 -6.373D+00 4.D-01 4.D-01 2.D+09 1.D-09  478P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 1.D+19 -2.293D+02 1.D+00 -6.373D+00 4.D-01 4.D-01 2.D+10 1.D-09  485P  0   0
 21 1.D+20 -2.293D+02 1.D+00 -6.373D+00 4.D-01 4.D-01 2.D+11 1.D-09  900P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.23

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   4652
 Subroutine evalg    (coded=T):    973
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  93429 (  4671 calls per constraint in average)
 Subroutine evaljac  (coded=T):   9711 (   485 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    899
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 97
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 3.3D-02
 Smallest constraints scale factor : 9.5D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -1.171D+02 4.D+00 -3.829D+00 2.D+00 2.D+00 9.D-01 2.D+00    0   0   0
  1 6.D+00 -3.630D+02 2.D+00 -1.187D+01 1.D+00 1.D+00 3.D+00 5.D-01   10C  0   0
  2 1.D+02 -2.013D+02 1.D+00 -6.581D+00 1.D+00 1.D+00 1.D-05 1.D-02   24C  0   0
  3 1.D+03 -2.000D+02 1.D+00 -6.540D+00 1.D+00 1.D+00 3.D-06 3.D-06   31C  0   0
  4 1.D+04 -2.000D+02 1.D+00 -6.540D+00 1.D+00 1.D+00 3.D-10 7.D-10   33C  0   0
  5 1.D+05 -2.000D+02 1.D+00 -6.540D+00 1.D+00 1.D+00 8.D-05 7.D-10   33C  0   0
  6 1.D+06 -2.000D+02 1.D+00 -6.540D+00 1.D+00 1.D+00 2.D-05 7.D-11   34C  0   0
  7 1.D+07 -2.000D+02 1.D+00 -6.540D+00 1.D+00 1.D+00 6.D-05 7.D-12   35C  0   0
  8 1.D+08 -2.000D+02 1.D+00 -6.540D+00 1.D+00 1.D+00 2.D-05 5.D-13   36C  0   0
  9 1.D+09 -2.000D+02 1.D+00 -6.540D+00 1.D+00 1.D+00 2.D-05 2.D-14   37C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 1.D+10 -2.000D+02 1.D+00 -6.540D+00 1.D+00 1.D+00 7.D-06 2.D-15   38C  0   0
 11 1.D+11 -2.000D+02 1.D+00 -6.540D+00 1.D+00 1.D+00 3.D-05 3.D-16   39C  0   0
 12 1.D+12 -2.000D+02 1.D+00 -6.540D+00 1.D+00 1.D+00 3.D-05 0.D+00   40C  0   0
 13 1.D+13 -2.000D+02 1.D+00 -6.540D+00 1.D+00 1.D+00 3.D-05 0.D+00   40C  0   0
 14 1.D+14 -2.000D+02 1.D+00 -6.540D+00 1.D+00 1.D+00 3.D-05 0.D+00   40C  0   0
 15 1.D+15 -2.000D+02 1.D+00 -6.540D+00 1.D+00 1.D+00 3.D-05 0.D+00   40C  0   0
 16 1.D+16 -2.000D+02 1.D+00 -6.540D+00 1.D+00 1.D+00 3.D-05 0.D+00   40C  0   0
 17 1.D+17 -2.000D+02 1.D+00 -6.540D+00 1.D+00 1.D+00 3.D-05 0.D+00   40C  0   0
 18 1.D+18 -2.000D+02 1.D+00 -6.540D+00 1.D+00 1.D+00 3.D-05 0.D+00   40C  0   0
 19 1.D+19 -2.000D+02 1.D+00 -6.540D+00 1.D+00 1.D+00 3.D-05 0.D+00   40C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 1.D+20 -2.000D+02 1.D+00 -6.540D+00 1.D+00 1.D+00 3.D-05 0.D+00   40C  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.00

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):    135
 Subroutine evalg    (coded=T):    109
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):   3057 (   152 calls per constraint in average)
 Subroutine evaljac  (coded=T):   1164 (    58 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):     45
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 98
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 2.8D-02
 Smallest constraints scale factor : 8.9D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -1.104D+02 4.D+00 -3.044D+00 4.D+00 4.D+00 9.D-01 4.D+00    0   0   0
  1 2.D+00 -6.507D+02 3.D+00 -1.794D+01 1.D+00 1.D+00 1.D+00 7.D-01   10C  0   0
  2 6.D+01 -2.989D+02 1.D+00 -8.244D+00 1.D+00 1.D+00 4.D-06 9.D-03   33C  0   0
  3 6.D+02 -2.978D+02 1.D+00 -8.211D+00 1.D+00 1.D+00 7.D-05 5.D-05   41C  0   0
  4 6.D+03 -2.978D+02 1.D+00 -8.211D+00 1.D+00 1.D+00 7.D-09 1.D-07   44C  0   0
  5 6.D+04 -2.978D+02 1.D+00 -8.211D+00 1.D+00 1.D+00 6.D-08 3.D-11   46C  0   0
  6 6.D+05 -2.978D+02 1.D+00 -8.211D+00 1.D+00 1.D+00 2.D-05 3.D-11   46C  0   0
  7 6.D+06 -2.978D+02 1.D+00 -8.211D+00 1.D+00 1.D+00 6.D-06 3.D-12   47C  0   0
  8 6.D+07 -2.978D+02 1.D+00 -8.211D+00 1.D+00 1.D+00 1.D-05 3.D-13   48C  0   0
  9 6.D+08 -2.978D+02 1.D+00 -8.211D+00 1.D+00 1.D+00 9.D-06 4.D-14   49C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 6.D+09 -2.978D+02 1.D+00 -8.211D+00 1.D+00 1.D+00 2.D-06 2.D-15   50C  0   0
 11 6.D+10 -2.978D+02 1.D+00 -8.211D+00 1.D+00 1.D+00 4.D-05 7.D-16   52C  0   0
 12 6.D+11 -2.978D+02 1.D+00 -8.211D+00 1.D+00 1.D+00 8.D+03 1.D-08   59P  0   0
 13 6.D+12 -2.978D+02 1.D+00 -8.211D+00 1.D+00 1.D+00 5.D+03 7.D-10   79P  0   0
 14 6.D+13 -2.978D+02 1.D+00 -8.211D+00 1.D+00 1.D+00 9.D+03 1.D-10  178P  0   0
 15 6.D+14 -2.978D+02 1.D+00 -8.211D+00 1.D+00 1.D+00 1.D+06 2.D-09  183P  0   0
 16 6.D+15 -2.978D+02 1.D+00 -8.211D+00 1.D+00 1.D+00 3.D+07 5.D-09  187P  0   0
 17 6.D+16 -2.978D+02 1.D+00 -8.211D+00 1.D+00 1.D+00 3.D+08 5.D-09  192P  0   0
 18 6.D+17 -2.978D+02 1.D+00 -8.211D+00 1.D+00 1.D+00 9.D+09 2.D-08  218P  0   0
 19 6.D+18 -2.978D+02 1.D+00 -8.211D+00 1.D+00 1.D+00 4.D+10 5.D-09  270P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 6.D+19 -2.978D+02 1.D+00 -8.211D+00 1.D+00 1.D+00 2.D+12 3.D-08  287P  0   0
 21 6.D+20 -2.978D+02 1.D+00 -8.211D+00 1.D+00 1.D+00 2.D+12 4.D-09  351P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.09

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   1765
 Subroutine evalg    (coded=T):    430
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  35858 (  1792 calls per constraint in average)
 Subroutine evaljac  (coded=T):   5329 (   266 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    350
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 99
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 2.5D-02
 Smallest constraints scale factor : 7.6D-02

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -1.393D+02 4.D+00 -3.528D+00 4.D+00 4.D+00 9.D-01 3.D+00    0   0   0
  1 4.D+00 -3.699D+02 1.D+00 -9.367D+00 1.D+00 1.D+00 1.D+00 3.D-01   10C  0   0
  2 6.D+01 -2.182D+02 1.D+00 -5.527D+00 1.D+00 1.D+00 1.D-05 6.D-03   57C  0   0
  3 6.D+02 -2.165D+02 1.D+00 -5.483D+00 1.D+00 1.D+00 5.D-05 2.D-05   66C  0   0
  4 6.D+03 -2.165D+02 1.D+00 -5.483D+00 1.D+00 1.D+00 6.D-06 8.D-09   68C  0   0
  5 6.D+04 -2.165D+02 1.D+00 -5.483D+00 1.D+00 1.D+00 4.D-05 7.D-10   69C  0   0
  6 6.D+05 -2.165D+02 1.D+00 -5.483D+00 1.D+00 1.D+00 2.D-05 8.D-11   70C  0   0
  7 6.D+06 -2.165D+02 1.D+00 -5.483D+00 1.D+00 1.D+00 3.D-05 6.D-12   71C  0   0
  8 6.D+07 -2.165D+02 1.D+00 -5.483D+00 1.D+00 1.D+00 5.D-05 1.D-12   72C  0   0
  9 6.D+08 -2.165D+02 1.D+00 -5.483D+00 1.D+00 1.D+00 4.D-05 1.D-13   73C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 6.D+09 -2.165D+02 1.D+00 -5.483D+00 1.D+00 1.D+00 3.D-05 9.D-15   74C  0   0
 11 6.D+10 -2.165D+02 1.D+00 -5.483D+00 1.D+00 1.D+00 7.D-05 8.D-16   75C  0   0
 12 6.D+11 -2.165D+02 1.D+00 -5.483D+00 1.D+00 1.D+00 2.D+03 3.D-09   89P  0   0
 13 6.D+12 -2.165D+02 1.D+00 -5.483D+00 1.D+00 1.D+00 3.D-03 1.D-12   94P  0   0
 14 6.D+13 -2.165D+02 1.D+00 -5.483D+00 1.D+00 1.D+00 8.D+05 3.D-08   98P  0   0
 15 6.D+14 -2.165D+02 1.D+00 -5.483D+00 1.D+00 1.D+00 5.D+05 8.D-10  127P  0   0
 16 6.D+15 -2.165D+02 1.D+00 -5.483D+00 1.D+00 1.D+00 9.D+07 4.D-08  188P  0   0
 17 6.D+16 -2.165D+02 1.D+00 -5.483D+00 1.D+00 1.D+00 1.D+09 4.D-08  192P  0   0
 18 6.D+17 -2.165D+02 1.D+00 -5.483D+00 1.D+00 1.D+00 2.D+09 8.D-09  199P  0   0
 19 6.D+18 -2.165D+02 1.D+00 -5.483D+00 1.D+00 1.D+00 3.D+10 9.D-09  209P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 6.D+19 -2.165D+02 1.D+00 -5.483D+00 1.D+00 1.D+00 2.D+11 6.D-09  245P  0   0
 21 6.D+20 -2.165D+02 1.D+00 -5.483D+00 1.D+00 1.D+00 7.D+09 3.D-11  274P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.06

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):   1317
 Subroutine evalg    (coded=T):    364
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  27109 (  1355 calls per constraint in average)
 Subroutine evaljac  (coded=T):   4278 (   213 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    271
 Subroutine evalhlp  (coded=F):      0

(ellipses) SEED = 100
ALGENCAN: 
 ==============================================================================
 This is ALGENCAN 2.4.0.
 ALGENCAN, an augmented Lagrangian method for nonlinear programming, is part of
 the TANGO Project: Trustable Algorithms for Nonlinear General Optimization.
 See http://www.ime.usp.br/~egbirgin/tango/ for details.
 ==============================================================================

 Specification file algencan.dat is being used.

 ALGENCAN PARAMETERS:
 firstde  =                    T
 truehl   =                    T
 hptype   =               TRUEHP
 innslvr  =                   TR
 sclsys   =                    T
 skipacc  =                    F
 lsssub   =                 MA57
 sclsub   =                 MA57
 rmfixv   =                    T
 slacks   =                    F
 scale    =                    T
 epsfeas  =           1.0000D-08
 epsopt   =           1.0000D-08
 efacc    =           1.0000D-04
 eoacc    =           1.0000D-04
 iprint   =                   10
 ncomp    =                    6

 Number of variables               :      15
 Number of equality constraints    :       5
 Number of inequality constraints  :      15
 Number of bound constraints       :      10

 Number of removed fixed variables :       0

 Objective function scale factor   : 6.0D-02
 Smallest constraints scale factor : 1.5D-01

 Entry to ALGENCAN.
 Number of variables  :      15
 Number of constraints:      20

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
  0        -5.114D+01 3.D+00 -3.065D+00 2.D+00 2.D+00 1.D+00 2.D+00    0   0   0
  1 5.D+00 -3.009D+02 1.D+00 -1.804D+01 9.D-01 9.D-01 1.D+00 6.D-01   10C  0   0
  2 2.D+02 -1.926D+02 1.D+00 -1.155D+01 9.D-01 9.D-01 2.D-09 3.D-02   22C  0   0
  3 2.D+03 -1.919D+02 1.D+00 -1.150D+01 9.D-01 9.D-01 6.D-07 5.D-04   25C  0   0
  4 2.D+04 -1.919D+02 1.D+00 -1.150D+01 9.D-01 9.D-01 2.D-10 1.D-05   28C  0   0
  5 2.D+05 -1.919D+02 1.D+00 -1.150D+01 9.D-01 9.D-01 5.D-06 3.D-07   30C  0   0
  6 2.D+06 -1.919D+02 1.D+00 -1.150D+01 9.D-01 9.D-01 1.D-09 6.D-09   32C  0   0
  7 2.D+07 -1.919D+02 1.D+00 -1.150D+01 9.D-01 9.D-01 2.D-08 1.D-10   34C  0   0
  8 2.D+08 -1.919D+02 1.D+00 -1.150D+01 9.D-01 9.D-01 1.D-07 3.D-12   36C  0   0
  9 2.D+09 -1.919D+02 1.D+00 -1.150D+01 9.D-01 9.D-01 6.D-06 8.D-14   38C  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 10 2.D+10 -1.919D+02 1.D+00 -1.150D+01 9.D-01 9.D-01 3.D-05 3.D-15   40C  0   0
 11 2.D+11 -1.919D+02 1.D+00 -1.150D+01 9.D-01 9.D-01 7.D-05 3.D-16   42C  0   0
 12 2.D+12 -1.919D+02 1.D+00 -1.150D+01 9.D-01 9.D-01 1.D-03 7.D-16   45P  0   0
 13 2.D+13 -1.662D+02 1.D+00 -9.964D+00 9.D-01 9.D-01 1.D+03 2.D-02   69P  0   0
 14 2.D+14 -1.671D+02 1.D+00 -1.002D+01 9.D-01 9.D-01 4.D-01 2.D-04   96P  0   0
 15 2.D+15 -1.671D+02 1.D+00 -1.001D+01 9.D-01 9.D-01 9.D-01 2.D-06  108P  0   0
 16 2.D+16 -1.671D+02 1.D+00 -1.001D+01 9.D-01 9.D-01 1.D+01 2.D-08  116P  0   0
 17 2.D+17 -1.671D+02 1.D+00 -1.001D+01 9.D-01 9.D-01 4.D+02 1.D-10  122P  0   0
 18 2.D+18 -1.671D+02 1.D+00 -1.001D+01 9.D-01 9.D-01 6.D+03 1.D-12  132P  0   0
 19 2.D+19 -1.671D+02 1.D+00 -1.001D+01 9.D-01 9.D-01 8.D+04 1.D-14  137P  0   0

out penalt  objective infeas  scaled    scaled infeas norm   |Grad| inner Newton
ite         function  ibilty  obj-funct infeas +compl graLag infeas totit forKKT
 20 2.D+20 -1.671D+02 1.D+00 -1.001D+01 9.D-01 9.D-01 4.D+05 7.D-15  144P  0   0

 Flag of ALGENCAN: The penalty parameter is too large.
 The problem may be infeasibile or bad scaled. Further analysis is required.

 Total CPU time in seconds:     0.02

 User-provided subroutines calls counters: 

 Subroutine evalf    (coded=T):    527
 Subroutine evalg    (coded=T):    216
 Subroutine evalh    (coded=F):      0
 Subroutine evalc    (coded=T):  11068 (   553 calls per constraint in average)
 Subroutine evaljac  (coded=T):   2451 (   122 calls per constraint in average)
 Subroutine evalhc   (coded=F):      0 (     0 calls per constraint in average)
 Subroutine evalfc   (coded=F):      0
 Subroutine evalgjac (coded=F):      0
 Subroutine evalhl   (coded=T):    142
 Subroutine evalhlp  (coded=F):      0

