[Couenne-tickets] [Couenne, a solver for non-convex MINLP problems] #16: Problems with COUENNE when constraints are swapped

[Couenne, a solver for non-convex MINLP problems]

#16: Problems with COUENNE when constraints are swapped
------------------------+---------------------------------------------------
 Reporter:  linh        |       Owner:  somebody
     Type:  defect      |      Status:  new     
 Priority:  major       |   Milestone:          
Component:  component1  |     Version:          
 Keywords:              |  
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 I am using AMPL and COUENNE with a very small example

 {{{
 var x1;
 var x2;

 minimize error: (x1 - 1)^2;

 subject to condition1: 0.0002612 + 1.43476/(1 + 100*(x2*0.3)^2) - 0.21*x1
 = 0;

 subject to condition2: 0.0001974 + 0.81608/(1 + 100*x1^2) - 0.2*x2 = 0;
 }}}

 COUENNE can solve and return the results well but when I swap two
 conditions (see below), COUENNE returns the message "The LP relaxation is
 infeasible or too expensive" and then terminates without returning any
 solution.

 {{{
 var x1;
 var x2;

 minimize error: (x1 - 1)^2;

 subject to condition2: 0.0001974 + 0.81608/(1 + 100*x1^2) - 0.2*x2 = 0;

 subject to condition1: 0.0002612 + 1.43476/(1 + 100*(x2*0.3)^2) - 0.21*x1
 = 0;
 }}}

 I write their .nl files and realize that AMPL writes the dual initial
 guess and primal initial guess for the first case into the .nl file

 {{{
 d2
 0 0
 1 0
 x2
 0 6.833221401328508
 1 0.00186069279294463
 }}}

 while AMPL does not do that for the second case.

 I also tried these examples with MINOS and they still can solve both
 cases.

 Could you please explain to me what does the message "The LP relaxation is
 infeasible or too expensive" mean and why does it appear in the case we
 swap constraints?

 Thank you very much,

 Linh

-- 
Ticket URL: <https://projects.coin-or.org/Couenne/ticket/16>
Couenne, a solver for non-convex MINLP problems <https://projects.coin-or.org/Couenne>
Couenne, a solver for non-convex MINLP problems