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CPLEX: Make adding mulitple objectives consistent with adding one objective

In the Java API for CPLEX (presumably similar in other APIs), it is possible to create an objective and add it to a model in one function call, using overloads of IloCplexModeler.addMinimize() and .addMaximize() that take an IloNumExpr argument. Doing the same with multiple objectives requires chaining function calls (e.g. staticLex() -> minimize() -> addMinimize()). This could (should?) be simplified.

  • Avatar32.5fb70cce7410889e661286fd7f1897de Guest
  • Sep 1 2020
  • Under review
Who would benefit from this IDEA? Anyone programming multiobjective models in CPLEX using a relevant API.
How should it work?

Add overloads of addMinimize() and addMaximize() that accept IloCplexMultiCriterionExpr in lieu of IloNumExpr.

Idea Priority Low
Priority Justification There is currently a straightforward, if mildly tedious, workaround, once you realize the "obvious" way (addMinimize(staticLex(...))) does not work.
Customer Name Paul Rubin
  • Attach files
  • Avatar40.8f183f721a2c86cd98fddbbe6dc46ec9
    Guest commented
    1 Oct 06:46am

    There is a very similar issue with the Python API (docplex).

    I have a model with some "hard" constraints, and 0 or more "soft" constraints. The problem is that I don't have a good interface in docplex for setting those constraints.

    In the case of 2 or more constraints, I use maximize_static_lex (the first constraint is more important then the second, which is more important than the third, and so on...). But if I try to use it with just 1 constraint, I get this error:

    Error: Multi objective must have at least 2 criteria.

    My request is to extend it so that if I call maximize_static_lex() with a list of length 1 it will behave like maximize(). Additionally, if the list is empty it will not do anything. If this is too difficult, then at least it should give a better error message, right when calling maximize_static_lex() and not on solve().

    Simple example:

    mdl = CpoModel()

    x = mdl.integer_var(min=0, max=9, name="x")

    y = mdl.integer_var(min=0, max=9, name="y")

    mdl.add(x + y < 15)

    mdl.add(x <= y)

    mdl.add(mdl.maximize_static_lex([x != y]))

    msol = mdl.solve(TimeLimit=10)‚Äč

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