Decision Optimization

Decision Optimization

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A model CPLEX has problem in finding lower bound and closing the gap

  • 1.  A model CPLEX has problem in finding lower bound and closing the gap

    Posted Fri September 25, 2020 01:36 AM
    Hello, everyone:
         I'm solving a MILP model whose native lower bound (via linear relaxation) is very poor. We could provide a lower bound by providing a given value (derived based on the problem itself). I know that directly adding a numerical lower bound on the objective may make no good (sometimes lead to a worse case by misleading the search produce). I try the both cases: with and without the numeric lower bound.  However, in neither case the CPLEX find the optimal solution in more than ten hours with out of memory. 

       My problem is what makes my specific model so hard to solve? I attached my mode files for reference.

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    Feng
    Researcher
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    #DecisionOptimization


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