[Couenne-tickets] [Couenne, a solver for non-convex MINLP problems] #14: feasible model declared infeasible

Couenne, a solver for non-convex MINLP problems coin-trac at coin-or.org
Sat Sep 24 08:23:00 EDT 2011


#14: feasible model declared infeasible
-------------------------+--------------------------------------------------
  Reporter:  stefan      |       Owner:  somebody
      Type:  defect      |      Status:  new     
  Priority:  major       |   Milestone:          
 Component:  component1  |     Version:          
Resolution:              |    Keywords:          
-------------------------+--------------------------------------------------

Comment (by pbelotti):

 Hi,

 unfortunately I can't reproduce the problem. Below is the output I get
 with stable/0.4 with no couenne.opt file.

 {{{
 Couenne  --  an Open-Source solver for Mixed Integer Nonlinear
 Optimization
 Mailing list: couenne at list.coin-or.org
 Instructions: http://www.coin-or.org/Couenne
 couenne:
 ANALYSIS TEST: NLP0012I
               Num      Status      Obj             It       time
 Location
 NLP0014I             1         OPT 1.4031777e-205.5g        5 0g
 Coin0506I Presolve 4 (-16) rows, 2 (-34) columns and 8 (-54) elements
 Clp0006I 0  Obj 0 Primal inf 0.0001748 (2)
 Clp0006I 2  Obj 1.995e-20
 Clp0000I Optimal - objective value 0
 Clp0032I Optimal objective 0 - 2 iterations time 0.002, Presolve 0.00
 Clp0000I Optimal - objective value 0
 Cbc0012I Integer solution of 1.403175e-20 found by Couenne Rounding NLP
 after 0 iterations and 0 nodes (0.00 seconds)
 NLP0014I             2         OPT 2.7792587e-245.5g       14 0g
 Clp0001I Primal infeasible - objective value 0
 Clp0001I Primal infeasible - objective value 0
 Clp0006I 0  Obj 0
 Clp0006I 0  Obj 0
 Clp0000I Optimal - objective value 0
 Cbc0001I Search completed - best objective 1.403175042267959e-20, took 0
 iterations and 0 nodes (0.01 seconds)
 Cbc0035I Maximum depth 0, 0 variables fixed on reduced cost

         "Finished"

 couenne: Optimal
 }}}

 You may want to disable some of the new feature to check which is
 responsible. Try for instance

 {{{
 use_semiaux no
 }}}

 Regards,
 Pietro

-- 
Ticket URL: <https://projects.coin-or.org/Couenne/ticket/14#comment:1>
Couenne, a solver for non-convex MINLP problems <https://projects.coin-or.org/Couenne>
Couenne, a solver for non-convex MINLP problems



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