[Ipopt] IPOPT takes very long before the first iteration

Sebastian Walter walter at mathematik.hu-berlin.de
Tue Sep 29 07:23:22 EDT 2009


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My speculative guess: It's the derivative checker of IPOPT that is the resource hog.
Depending on the dimension of your problem, the computation of finite differences approximations of gradient and jacobian
can take much longer than the evaluation your implemented  gradient and jacobian function.

The derivative check is performed once before the iteration starts.


regards,
Sebastian




Uwe Nowak schrieb:
> Hello!
> 
> I am using IPOPT and really like the solver. But with larger problem
> instances the solver takes very long time before the first iteration.
> 
> Below there is the output. After the first line ("This is IPOPT...") the
> solver takes (estimated) 350 CPU seconds.
> 
> What does IPOPT do there? Is there a way to speed this part of IPOPT up?
> The Iterations itself are fast enough.
> 
> I am using IPOPT to successively solve nonlinear problems that have 
> similar, but not equal structure. So I usually expect only few 
> iterations to be
> necessary.
> 
> Thank you,
> Uwe Nowak
> 
> 
> ------------------------- OUTPUT ------------------------------
> 
> 
> This is Ipopt version 3.7.0, running with linear solver ma27.
> 
> Number of nonzeros in equality constraint Jacobian...: 196
> Number of nonzeros in inequality constraint Jacobian.: 13624
> Number of nonzeros in Lagrangian Hessian.............: 0
> 
> Total number of variables............................: 180
>   variables with only lower bounds: 0
>   variables with lower and upper bounds: 0
>   variables with only upper bounds: 0
> Total number of equality constraints.................: 49
> Total number of inequality constraints...............: 1703
>   inequality constraints with only lower bounds: 1703
>   inequality constraints with lower and upper bounds: 0
>   inequality constraints with only upper bounds: 0
> 
> [...]
> 
> Number of Iterations....: 15
> 
> [...]
> 
> Number of objective function evaluations = 18
> Number of objective gradient evaluations = 16
> Number of equality constraint evaluations = 18
> Number of inequality constraint evaluations = 18
> Number of equality constraint Jacobian evaluations = 16
> Number of inequality constraint Jacobian evaluations = 16
> Number of Lagrangian Hessian evaluations = 0
> Total CPU secs in IPOPT (w/o function evaluations) = 392.561
> Total CPU secs in NLP function evaluations = 8.939
> 
> EXIT: Optimal Solution Found.
> 
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