Decision Optimization

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SOCP problem solved with CPLEX/AMPL it´s 10 times faster than when is solved with CPLEX/MATLAB, why?

  • 1.  SOCP problem solved with CPLEX/AMPL it´s 10 times faster than when is solved with CPLEX/MATLAB, why?

    Posted Tue November 10, 2020 11:38 AM

    I solved an optimal power flow (OPF) problem modeled as a second-order cone programming (SOCP). At first I solved using solver CPLEX in AMPL lenguage, and took 0.08s; then I solved the same problem with CPLEX for Matlab (command cplexqcp) and took 0.86s. Times shown correspond only to the times demand by the solver (CPLEX). Does anyone know what makes such a time difference?

    Time results for CPLEX/AMPL:

    Elapsed AMPL time : 0.430s
    Elapsed Solve time : 0.080s
    Elapsed CPU time: 0.510s

    Time results for CPLEX/MATLAB:

    tic
    [x,fval]=cplexqcp([],f,[],[],Aeq,beq,l,Qc,r,Li,Ls);
    toc :
    Elapsed time is 0.860856 seconds.

    Note: The problem has 542 variables.



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    Jonathan Ayala Marcelo
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    #DecisionOptimization


  • 2.  RE: SOCP problem solved with CPLEX/AMPL it´s 10 times faster than when is solved with CPLEX/MATLAB, why?

    Posted Tue November 10, 2020 02:08 PM
    Duplicate of this post.

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    Paul Rubin
    Professor Emeritus
    Michigan State University
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