[Ipopt] How to detect which constraints not satisfying Linear Independence Constraint Qualification?
Andreas Waechter
andreasw at watson.ibm.com
Fri Feb 26 17:07:05 EST 2010
Hi James,
I noticed in your output that your restoration phase failure is actually
for the restoration phase inside the restoration phase. The restoration
phase problem by construction satisfies LICQ, so this cannot really be the
issue. Maybe your constraint function are just very nasty (I assume you
verified that the derivative checker does not compain, and that there are
no "if" statements in the computation of your functions that might make
the problem non-smooth). Beside suggesting to try to formulate the
constraints in a different way, I don't know what to propose. You might
want to check if other NLP solvers can solve your problem.
Regards,
Andreas
On Tue, 9 Feb 2010, James Henderson wrote:
> Dear all,
>
> I have many constraint functions, but I suppose they are all linear independent, but there still have a failed restoration.
> Does anyone know how to detect which constraints not satisfying Linear Independence Constraint Qualification?
> Thank you.
>
> James
>
> This is Ipopt version 3.8.1, running with linear solver ma27.
>
> Number of nonzeros in equality constraint Jacobian...: 9672
> Number of nonzeros in inequality constraint Jacobian.: 38340
> Number of nonzeros in Lagrangian Hessian.............: 0
>
> Total number of variables............................: 2136
> variables with only lower bounds: 0
> variables with lower and upper bounds: 0
> variables with only upper bounds: 0
> Total number of equality constraints.................: 806
> Total number of inequality constraints...............: 4260
> inequality constraints with only lower bounds: 0
> inequality constraints with lower and upper bounds: 0
> inequality constraints with only upper bounds: 4260
>
> iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_pr ls
> 0 1.8076131e+004 8.53e-003 2.21e+001 0.0 0.00e+000 - 0.00e+000 0.00e+000 0
> 1 6.1451386e+002 5.88e-001 8.75e+000 -0.2 2.22e+001 - 4.90e-001 4.18e-001f 1
> ...........
> 1380r4.1766689e+002 9.97e-001 1.21e-001 -4.9 8.64e-001 - 1.00e+000 1.00e+000h 1
> 1381r4.1617759e+002 9.50e-001 1.40e+000 -4.9 6.68e-001 - 1.00e+000 1.00e+000h 1
> Restoration phase converged to a feasible point that is
> unacceptable to the filter for the original problem.
> Restoration phase in the restoration phase failed.
>
> Number of Iterations....: 1381
>
> (scaled) (unscaled)
> Objective...............: 4.1431717107537929e+002 4.1431717107537929e+002
> Dual infeasibility......: 4.7797490421788211e+000 4.7797490421788211e+000
> Constraint violation....: 4.0595912702112713e-005 4.0595912702112713e-005
> Complementarity.........: 7.7917756206222183e-006 7.7917756206222183e-006
> Overall NLP error.......: 4.7797490421788211e+000 4.7797490421788211e+000
>
>
> Number of objective function evaluations = 2855
> Number of objective gradient evaluations = 196
> Number of equality constraint evaluations = 2856
> Number of inequality constraint evaluations = 2856
> Number of equality constraint Jacobian evaluations = 1386
> Number of inequality constraint Jacobian evaluations = 1386
> Number of Lagrangian Hessian evaluations = 0
> Total CPU secs in IPOPT (w/o function evaluations) = 281.311
> Total CPU secs in NLP function evaluations = 11.907
>
> EXIT: Restoration Failed!
>
>
>
>
>
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