[Ipopt] Question about CPU time in NLP function evaluations

[Ahn, Tae-Hyuk]

Hello All,

I am a new user and fan of IPOPT. I have a question about CPU time for NLP function evaluations. 

My problem has dynamic variables with complex objective function. Below is the variable info of one example.

---------------------------------------------------------------------------
Number of nonzeros in equality constraint Jacobian...:     1291
Number of nonzeros in inequality constraint Jacobian.:        0
Number of nonzeros in Lagrangian Hessian.............:   833986

Total number of variables............................:     1291
                     variables with only lower bounds:        0
                variables with lower and upper bounds:     1291
                     variables with only upper bounds:        0
Total number of equality constraints.................:        1
Total number of inequality constraints...............:        0
        inequality constraints with only lower bounds:        0
   inequality constraints with lower and upper bounds:        0
        inequality constraints with only upper bounds:        0
---------------------------------------------------------------------------

After IPOPT solves the problem, I satisfy the results. The problem is, however, elapsed time.

---------------------------------------------------------------------------
Number of Iterations....: 22
Total CPU secs in IPOPT (w/o function evaluations)   =     60.527
Total CPU secs in NLP function evaluations           =  12798.083
---------------------------------------------------------------------------

As you see that, it took 3-4 hours to solve this problem. Especially, "NLP function evaluations" tool all of time.

Let's assume that f, grad_f, g, jac_g, and h are already optimized (that means I don't want to change them). How can I reduce the elapsed time? Can I "turn off" the step "NLP function evaluation"?

If you have any suggestion, please let me know.

Thank you very much!

Sincerely,

Ted