[Ipopt] ipopt: The problem FAILED

Joris Kinable deus87 at gmail.com
Tue Apr 2 13:01:47 EDT 2013


I've implemented a small NLP model into ipopt using the Java interface.
When I hit solve, the program terminates with the following message:

"The problem FAILED".

I'm trying to debug the model to see what's wrong. Hence, I've set the
objective function to a fixed constant, thereby turning the optimization
problem into a constraint satisfaction problem. Next, I've initialized the
problem with a feasible solution, i.e. a solution which satisfies all
constraints. So basically, the optimizer could return the initial solution
immediately; no optimization is required. Still, I get the message that the
problem fails (part of the log is included at the end of this mail).

1. Why doesn't the solver return the initial solution, as it is a feasible

2. What could cause ipopt to return 'The problem Failed', i.e. what should
I debug? I manually checked that all my constraints are feasible, as well
as the variable bounds.

3. The logger mentions that the search direction becomes too small. Why
can't it identify that it has found a local/global optimum?




Number of Iterations....: 263

                                   (scaled)                 (unscaled)
Objective...............:   1.0000000000000000e+00    1.0000000000000000e+00
Dual infeasibility......:   1.0999505370964350e-05    1.0999505370964350e-05
Constraint violation....:   0.0000000000000000e+00    0.0000000000000000e+00
Complementarity.........:   9.0909090909090941e-10    9.0909090909090941e-10
Overall NLP error.......:   1.0999505370964350e-05    1.0999505370964350e-05

Number of objective function evaluations             = 289
Number of objective gradient evaluations             = 55
Number of equality constraint evaluations            = 0
Number of inequality constraint evaluations          = 289
Number of equality constraint Jacobian evaluations   = 0
Number of inequality constraint Jacobian evaluations = 266
Number of Lagrangian Hessian evaluations             = 264
Total CPU secs in IPOPT (w/o function evaluations)   =      0.180
Total CPU secs in NLP function evaluations           =      0.016

EXIT: Search Direction is becoming Too Small.
Obj: 1.0
Circle 0: (-41.30054873354737,3.222049686239637), r:10.0
Circle 1: (0.49442322310794523,-26.773758302392906), r:10.0
Circle 2: (-44.843610818313735,-23.277936648765795), r:10.0
Circle 3: (-22.36952325252463,-36.936746537913145), r:10.0

*** The problem FAILED!
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