Topic
3 replies Latest Post - ‏2013-09-26T13:18:37Z by AlexFleischer
GrEm
GrEm
2 Posts
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Pinned topic Indicator constraints relaxation in OPL

‏2013-07-31T16:04:31Z |
Hi
I am solving a problem with piecewise linear constraints in OPL using OPL script.
One of thoses constraints is non-convex and yields to a MIP with indicator variables.
I would like to relax all indicator constraints and solve the linear relaxation of the problem.
Is there a way to do that ?

convertAllIntVars() does not work on indicator variables/constraints apparently.

I found a reference on the the following function, but I can't make it work in OPL.
c.indicator_constraints.delete()

(found in CPLEX Python API Reference Manual)

Thanks

 

Updated on 2013-08-08T13:23:50Z at 2013-08-08T13:23:50Z by GrEm
  • AlexFleischer
    AlexFleischer
    1076 Posts
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    Re: Indicator constraints relaxation in OPL

    ‏2013-09-03T16:19:40Z  in response to GrEm

    Hi,

     

    do you want to do this in order to have some sensitivity analysis for a solution ?

     

    regards

    • GrEm
      GrEm
      2 Posts
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      Re: Indicator constraints relaxation in OPL

      ‏2013-09-23T14:18:57Z  in response to AlexFleischer

      Hi

      I would like to solve a relaxed version of the subproblem at some iterations, to speed up the computation.

      Currently I have to re-generate the whole problem when I want to switch from the MIP formulation (with piecewise() hence with indicator constraints) to the LP relaxation.

      I lose quite a lot of time in the generate() function, while only a few indicator constraints need to be relaxed.

      Thanks