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E04ST, Interior point method for large-scale nonlinear optimization problems
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Begin of Options
Print File = 50 * U
Print Level = 2 * U
Monitoring File = 51 * U
Monitoring Level = 5 * U
Infinite Bound Size = 1.00000E+20 * d
Task = Minimize * d
Stats Time = No * d
Time Limit = 6.00000E+01 * U
Verify Derivatives = No * d
Hessian Mode = Auto * d
Matrix Ordering = Auto * d
Outer Iteration Limit = 26 * U
Stop Tolerance 1 = 2.50000E-08 * U
End of Options
******************************************************************************
This program contains Ipopt, a library for large-scale nonlinear optimization.
Ipopt is released as open source code under the Eclipse Public License (EPL).
For more information visit http://projects.coin-or.org/Ipopt
******************************************************************************
This version is built and supported by Numerical Algorithms Group (NAG) Ltd.
For support email support@nag.co.uk
******************************************************************************
This is Ipopt version 3.12.4, running with linear solver ma97.
Number of nonzeros in equality constraint Jacobian...: 4
Number of nonzeros in inequality constraint Jacobian.: 8
Number of nonzeros in Lagrangian Hessian.............: 10
Total number of variables............................: 4
variables with only lower bounds: 4
variables with lower and upper bounds: 0
variables with only upper bounds: 0
Total number of equality constraints.................: 1
Total number of inequality constraints...............: 2
inequality constraints with only lower bounds: 2
inequality constraints with lower and upper bounds: 0
inequality constraints with only upper bounds: 0
iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_pr ls
0 1.3080000e+02 3.00e+00 5.90e-01 -1.0 0.00e+00 - 0.00e+00 0.00e+00 0
1 7.8782624e+01 9.98e-01 2.36e-01 -1.0 4.00e+01 - 9.67e-01 6.67e-01f 1
2 3.6879120e+01 0.00e+00 1.51e+00 -1.0 4.87e+01 - 5.06e-01 1.00e+00f 1
3 2.9955743e+01 0.00e+00 7.36e-02 -1.0 1.38e+01 - 1.00e+00 9.87e-01f 1
4 2.9945313e+01 0.00e+00 3.98e-05 -1.7 8.36e-02 - 1.00e+00 1.00e+00h 1
5 2.9895752e+01 1.81e-04 1.15e-02 -3.8 5.43e-02 - 9.54e-01 9.93e-01f 1
6 2.9894810e+01 0.00e+00 9.79e-07 -3.8 2.48e-03 - 1.00e+00 1.00e+00h 1
7 2.9894383e+01 0.00e+00 3.63e-08 -5.7 5.21e-04 - 1.00e+00 1.00e+00h 1
8 2.9894378e+01 0.00e+00 6.72e-12 -8.6 7.11e-06 - 1.00e+00 1.00e+00h 1
Number of Iterations....: 8
(scaled) (unscaled)
Objective...............: 2.9894378048973934e+01 2.9894378048973934e+01
Dual infeasibility......: 6.7175978109862574e-12 6.7175978109862574e-12
Constraint violation....: 0.0000000000000000e+00 0.0000000000000000e+00
Complementarity.........: 2.5601472143227907e-09 2.5601472143227907e-09
Overall NLP error.......: 2.5601472143227907e-09 2.5601472143227907e-09
Number of objective function evaluations = 9
Number of objective gradient evaluations = 9
Number of equality constraint evaluations = 9
Number of inequality constraint evaluations = 9
Number of equality constraint Jacobian evaluations = 9
Number of inequality constraint Jacobian evaluations = 9
Number of Lagrangian Hessian evaluations = 8
Total CPU secs in IPOPT (w/o function evaluations) = 0.018
Total CPU secs in NLP function evaluations = 0.000
EXIT: Optimal Solution Found.