Hi,<div>The limits are only checked after each nlp solve. You should not expect the time limit to be respected to the second.</div><div>Best,</div><div>Pierre<br><br><div class="gmail_quote">On Sat, Jul 4, 2009 at 2:06 PM, Giuseppe Aprea <span dir="ltr"><<a href="mailto:giuseppe.aprea@gmail.com">giuseppe.aprea@gmail.com</a>></span> wrote:<br>
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex;">HI,<br>
<br>
I am sorry for all these messages.<br>
<br>
Still solving a MINLP with B-BB. My problem now is why both<br>
<br>
bonmin.time_limit 1<br>
bonmin.iteration_limit 10<br>
<br>
<br>
seem not to work even if put together?. For the Time limit I am not<br>
sure if we are talking about<br>
cputime or whatever but when I stopped (ctrl-c) the computation all<br>
values where above my limit<br>
(see below). I have read the documentation and it seems that just one<br>
of the two limits should<br>
have worked. I also added the "\n" character at the and of the last<br>
line and the prefix "bonmin.".<br>
Can someone, please, suggest me a way to stop the computation?<br>
<br>
Many many thanks<br>
<br>
giuseppe<br>
<br>
<br>
WARNING: Tried to set option "print_level" to a value of "1",<br>
but the previous value is set to disallow clobbering.<br>
The setting will remain as: "print_level 6"<br>
<br>
List of options:<br>
<br>
Name Value # times used<br>
bonmin.algorithm = B-BB 1<br>
bonmin.bb_log_level = 4 2<br>
bonmin.iteration_limit = 10 1<br>
bonmin.number_before_trust = 1 0<br>
bonmin.number_strong_branch = 1000 0<br>
bonmin.time_limit = 1 1<br>
bonmin.variable_selection = nlp-strong-branching 0<br>
expect_infeasible_problem = yes 2<br>
gamma_phi = 1e-08 1<br>
gamma_theta = 0.0001 1<br>
mu_oracle = probing 2<br>
mu_strategy = adaptive 2<br>
print_level = 6 3<br>
print_solution = yes 1<br>
required_infeasibility_reduction = 0.1 0<br>
<br>
******************************************************************************<br>
This program contains Ipopt, a library for large-scale nonlinear optimization.<br>
Ipopt is released as open source code under the Common Public License (CPL).<br>
For more information visit <a href="http://projects.coin-or.org/Ipopt" target="_blank">http://projects.coin-or.org/Ipopt</a><br>
******************************************************************************<br>
<br>
NOTE: You are using Ipopt by default with the MUMPS linear solver.<br>
Other linear solvers might be more efficient (see Ipopt documentation).<br>
<br>
<br>
This is Ipopt version 3.6stable, running with linear solver mumps.<br>
<br>
Number of nonzeros in equality constraint Jacobian...: 10581<br>
Number of nonzeros in inequality constraint Jacobian.: 1684<br>
Number of nonzeros in Lagrangian Hessian.............: 1440<br>
<br>
Scaling parameter for objective function = 1.000000e+00<br>
Equality constraints are scaled with smallest scaling parameter is 1.000000e-01<br>
Inequality constraints are not scaled.<br>
Moved initial values of x sufficiently inside the bounds.<br>
<br>
<br>
....................................................................................<br>
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....................................................................................<br>
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<br>
<br>
<br>
**************************************************<br>
*** Update HessianMatrix for Iteration 138:<br>
**************************************************<br>
<br>
<br>
<br>
**************************************************<br>
*** Summary of Iteration: 138:<br>
**************************************************<br>
<br>
iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_pr ls<br>
138 -6.7209529e+01 3.64e-02 2.18e+06 1.0 9.05e-01 5.4 1.81e-01<br>
1.07e-01h 1 Fl<br>
<br>
**************************************************<br>
*** Beginning Iteration 138 from the following point:<br>
**************************************************<br>
<br>
Current barrier parameter mu = 1.0903679534902398e+01<br>
Current fraction-to-the-boundary parameter tau = 9.8999999999999999e-01<br>
<br>
||curr_x||_inf = 1.9661942024696255e+05<br>
||curr_s||_inf = 1.2178079283934749e+04<br>
||curr_y_c||_inf = 2.6443132699285839e+07<br>
||curr_y_d||_inf = 1.2624137038804408e+07<br>
||curr_z_L||_inf = 5.3355026600588057e+06<br>
||curr_z_U||_inf = 2.2719144233394220e+07<br>
||curr_v_L||_inf = 1.0903812213355341e-08<br>
||curr_v_U||_inf = 1.0900972670818821e+07<br>
<br>
<br>
***Current NLP Values for Iteration 138:<br>
<br>
(scaled) (unscaled)<br>
Objective...............: -6.7209528968436345e+01 -6.7209528968436345e+01<br>
Dual infeasibility......: 2.1777462890798487e+06 2.1777462890798487e+06<br>
Constraint violation....: 3.6405018980666198e-02 9.8824327150319968e-02<br>
Complementarity.........: 1.8107150690355127e+02 1.8107150690355127e+02<br>
Overall NLP error.......: 6.6624480905292455e+02 2.1777462890798487e+06<br>
<br>
<br>
<br>
<br>
**************************************************<br>
*** Update Barrier Parameter for Iteration 138:<br>
**************************************************<br>
<br>
Remaining in fixed mu mode.<br>
Barrier Parameter: 1.090368e+01<br>
<br>
**************************************************<br>
*** Solving the Primal Dual System for Iteration 138:<br>
**************************************************<br>
<br>
Number of doubles for MUMPS to hold factorization (INFO(9)) = 253214<br>
Number of integers for MUMPS to hold factorization (INFO(10)) = 142227<br>
In MumpsSolverInterface::Factorization: negevals_ = 3903, but<br>
numberOfNegEVals = 3353<br>
Factorization failed with retval = 2<br>
Number of doubles for MUMPS to hold factorization (INFO(9)) = 129365<br>
Number of integers for MUMPS to hold factorization (INFO(10)) = 138707<br>
In MumpsSolverInterface::Factorization: negevals_ = 3354, but<br>
numberOfNegEVals = 3353<br>
Factorization failed with retval = 2<br>
Number of doubles for MUMPS to hold factorization (INFO(9)) = 129365<br>
Number of integers for MUMPS to hold factorization (INFO(10)) = 138707<br>
<br>
<br>
real 2m40.741s<br>
user 1m46.039s<br>
sys 0m1.736s<br>
<br>
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</blockquote></div><br></div>