[Ipopt] Question on 'user requested stop'

[Victor Fachinotti]

Dear developers,

 

I am trying to solve a constrained NLP, where the starting point x0
satisfies all the constraints but it is far to be an optimum. 

 

I have set options.ipopt to the default values, except for
options.ipopt.hessian_approximation = 'limited-memory'. 

 

IPOPT exits without modifying x0 with info.status=5 (user requested stop).

 

I would appreciate your help to understand why this happens.

 

Yours,

 

 

Prof. Dr. Víctor D. Fachinotti

Centro de Investigación de Métodos Computacionales (CIMEC)

Universidad Nacional del Litoral (UNL)

Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) 

Predio CONICET “Dr. Alberto Cassano”

Colectora Ruta Nac. 168 s/n, Paraje El Pozo

3000, Santa Fe, Argentina

Tel: +54 342 4511594 x 7045

Fax: +54 342 4511169

 

 

PS: These are the messages I got:

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

 

This is Ipopt version 3.11.8, running with linear solver ma57.

 

Number of nonzeros in equality constraint Jacobian...:     9701

Number of nonzeros in inequality constraint Jacobian.:     3200

Number of nonzeros in Lagrangian Hessian.............:        0

 

Reallocating memory for MA57: lfact (155793)

Reallocating memory for MA57: lfact (324812)

Reallocating memory for MA57: lfact (493001)

Reallocating memory for MA57: lfact (681090)

Reallocating memory for MA57: lfact (2385003)

Reallocating memory for MA57: lfact (3591894)

Reallocating memory for MA57: lfact (7330350)

Reallocating memory for MA57: lfact (8969064)

Total number of variables............................:     6518

                     variables with only lower bounds:        0

                variables with lower and upper bounds:     6518

                     variables with only upper bounds:        0

Total number of equality constraints.................:     3318

Total number of inequality constraints...............:        1

        inequality constraints with only lower bounds:        0

   inequality constraints with lower and upper bounds:        0

        inequality constraints with only upper bounds:        1

 

iter    objective    inf_pr   inf_du lg(mu)  ||d||  lg(rg) alpha_du alpha_pr
ls

   0 8.2501468e-002 5.41e-013 1.00e+000   0.0 0.00e+000    -  0.00e+000
0.00e+000   0

 

Number of Iterations....: 0

 

                                   (scaled)                 (unscaled)

Objective...............:  8.2501467997805847e-002   8.2501467997805847e-002

Dual infeasibility......:  1.0000000000000000e+000   1.0000000000000000e+000

Constraint violation....:  5.4107912499765483e-013   5.4107912499765483e-013

Complementarity.........:  1.8929389054602732e+000   1.8929389054602732e+000

Overall NLP error.......:  1.8929389054602732e+000   1.8929389054602732e+000

 

 

Number of objective function evaluations             = 1

Number of objective gradient evaluations             = 1

Number of equality constraint evaluations            = 1

Number of inequality constraint evaluations          = 1

Number of equality constraint Jacobian evaluations   = 1

Number of inequality constraint Jacobian evaluations = 1

Number of Lagrangian Hessian evaluations             = 0

Total CPU secs in IPOPT (w/o function evaluations)   =      0.493

Total CPU secs in NLP function evaluations           =      0.010

 

EXIT: Stopping optimization at current point as requested by user.

 

 

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