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Losing multiobjective behavior after feasibility relaxation?

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2 comments

  • Eli Towle
    Gurobi Staff Gurobi Staff

    This is expected behavior - the feasibility relaxation creates a single objective to minimize the solution's violation of the original constraints with respect to the specified metric. Note that only \( \texttt{minrelax=False} \) is currently supported for multi-objective models.

    To evaluate your multiple objectives at the feasibility relaxation's solution, you can store each objective function as a LinExpr object, then call LinExpr.getValue() once the feasibility relaxation finishes solving. For example, the following code

    import gurobipy as gp

    # Build simple model
    m = gp.Model()
    x = m.addVars(3, name='x')
    m.addConstr(x[0] >= 20)
    m.addConstr(x[1] >= 10)
    m.addConstr(x[2] >= 5)

    # Store objectives as LinExpr objects
    obj1 = x[0] + x[2]
    obj2 = 2*x[1]

    # Solve feasibility relaxation (minrelax=False)
    # For illustrative purposes - our model is feasible
    m.feasRelaxS(0, False, True, True)
    m.optimize()

    # Evaluate objectives at current solution
    print(f'obj1 = {obj1.getValue()}')
    print(f'obj2 = {obj2.getValue()}')

    evaluates the two linear expressions given the feasibility relaxation solution:

    obj1 = 25.0
    obj2 = 20.0
    1
  • Vineet Nair
    Gurobi-versary
    First Comment
    First Question

    Yes, this is the kind of solution I was looking for. Thank you!

    0

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