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Very simple docplex : warmstart through API

  • 1.  Very simple docplex : warmstart through API

    Posted Tue February 18, 2020 04:10 AM

    Hi,

    let's go on with the example from https://www.linkedin.com/pulse/what-optimization-how-can-help-you-do-more-less-zoo-buses-fleischer/

     

    Warmstart is essential and let's see how we can do that through files with docplex.

    In https://www.ibm.com/developerworks/community/forums/html/topic?id=41691ae0-9179-4c5f-86cc-5f389cdfc394

    we saw how to do warm start with MST files , let's now use APIs in docplex

     

    from docplex.mp.model import Model

    mdl = Model(name='buses')
    nbbus40 = mdl.integer_var(name='nbBus40')
    nbbus30 = mdl.integer_var(name='nbBus30')
    mdl.add_constraint(nbbus40*40 + nbbus30*30 >= 300, 'kids')
    mdl.minimize(nbbus40*500 + nbbus30*400)

    warmstart=mdl.new_solution()
    warmstart.add_var_value(nbbus40,8)
    warmstart.add_var_value(nbbus30,0)
    mdl.add_mip_start(warmstart)


    sol=mdl.solve(log_output=True)

    for v in mdl.iter_integer_vars():
        print(v," = ",v.solution_value)

    gives

     

    1 of 1 MIP starts provided solutions.
    MIP start 'm1' defined initial solution with objective 4000.0000.

     

    and then we see

     

    MIP emphasis: balance optimality and feasibility.
    MIP search method: dynamic search.
    Parallel mode: deterministic, using up to 12 threads.
    Root relaxation solution time = 0.00 sec. (0.00 ticks)

            Nodes                                         Cuts/
       Node  Left     Objective  IInf  Best Integer    Best Bound    ItCnt     Gap

    *     0+    0                         4000.0000        0.0000           100.00%
          0     0     3750.0000     1     4000.0000     3750.0000        0    6.25%
    *     0+    0                         3900.0000     3750.0000             3.85%
    *     0     0      integral     0     3800.0000     3800.0000        0    0.00%
    Elapsed time = 0.09 sec. (0.02 ticks, tree = 0.01 MB, solutions = 3)

    Root node processing (before b&c):
      Real time             =    0.11 sec. (0.02 ticks)
    Parallel b&c, 12 threads:
      Real time             =    0.00 sec. (0.00 ticks)
      Sync time (average)   =    0.00 sec.
      Wait time (average)   =    0.00 sec.
                              ------------
    Total (root+branch&cut) =    0.11 sec. (0.02 ticks)
    nbBus40  =  6.0
    nbBus30  =  2.0

     

    regards

    PS:

    Many similar examples at https://www.linkedin.com/pulse/making-optimization-simple-python-alex-fleischer/

     

     

     


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    #DecisionOptimization


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