[Ipopt] [Jipopt] Slow running time on windows x64 ?

[Tony Kelman]

Try turning the option print_timing_statistics to yes to get a more detailed 
breakdown of where the time is getting spent. Your problem is reasonably big 
but that does seem like a lot of time for only 1 iteration.


-----Original Message----- 
From: Razafindrazaka, Faniry
Sent: Thursday, May 21, 2015 4:01 AM
To: ipopt at list.coin-or.org
Subject: [Ipopt] [Jipopt] Slow running time on windows x64 ?





Hi all,



I am running some optimization problem using jipopt x64bit on Eclipse 
with -Xmx6g. The Hessian and the Jacobians are sparse. I would like to ask 
if the following running time make sense I feel like it is slow and should 
be way faster than this. My fear is that the jni makes it slow.



******************************************************************************

This program contains Ipopt, a library for large-scale nonlinear 
optimization.

Ipopt is released as open source code under the Eclipse Public License 
(EPL).

         For more information visit http://projects.coin-or.org/Ipopt

******************************************************************************



NOTE: You are using Ipopt by default with the MUMPS linear solver.

      Other linear solvers might be more efficient (see Ipopt 
documentation).





This is Ipopt version 3.11.0, running with linear solver mumps.



Number of nonzeros in equality constraint Jacobian...:    55152

Number of nonzeros in inequality constraint Jacobian.:        0

Number of nonzeros in Lagrangian Hessian.............:    64386



Total number of variables............................:    18396

                     variables with only lower bounds:        0

                variables with lower and upper bounds:        0

                     variables with only upper bounds:        0

Total number of equality constraints.................:    18166

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



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

   0 1.5968735e+001 0.00e+000 1.54e-003  -1.0 0.00e+000    -  0.00e+000 
0.00e+000   0

   1 7.5745104e-004 1.99e-013 2.94e-017  -3.8 1.26e+002    -  1.00e+000 
1.00e+000f  1



Number of Iterations....: 1



                                   (scaled)                 (unscaled)

Objective...............:  7.5745104075694916e-004   7.5745104075694916e-004

Dual infeasibility......:  2.9381031841409916e-017   2.9381031841409916e-017

Constraint violation....:  1.9895196601282805e-013   1.9895196601282805e-013

Complementarity.........:  0.0000000000000000e+000   0.0000000000000000e+000

Overall NLP error.......:  1.9895196601282805e-013   1.9895196601282805e-013





Number of objective function evaluations             = 2

Number of objective gradient evaluations             = 2

Number of equality constraint evaluations            = 2

Number of inequality constraint evaluations          = 0

Number of equality constraint Jacobian evaluations   = 2

Number of inequality constraint Jacobian evaluations = 0

Number of Lagrangian Hessian evaluations             = 1

Total CPU secs in IPOPT (w/o function evaluations)   =     25.498

Total CPU secs in NLP function evaluations           =      3.551



EXIT: Optimal Solution Found.

Status    = 0

Obj Value = 7.574510407569492E-4



Kind Regards

Faniry











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