Objective function lower and upper bounds

[Romain Montagné]

Hello,

I would like to know if it is possible to do the following things with PuLp:

1. Give a lower/upper bound to the objective function, but not as an additional constraint (kind of like the fact that we can give lower and upper bounds to the variables beforehand).

2. If we decide to stop the solver before it reaches optimality with the "timeLimit" or "epgap" options, the output is the best integer found. Is it possible to get the best upper bound (if we are maximizing) or best lower bound (if we are minimizing) easily (by get I mean store it in a python variable)?

Thank you very much for your help,

Romain

[Stuart Mitchell]

Hi if you are using the gurobi or cplex solvers the actual solver model object should be available at

LpProblem.solverModel

Note this object is only created after a call to solve()

Stu

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Stuart Mitchell

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[Romain Montagné]

Thank you. Are there different methods/attributes to this object?

If I do

>>>   print.prob.solverModel

I get <cplex.Cplex object at 0x2de3a10>. How can I work with that?

Thanks

[Stuart Mitchell]

Refer to the cplex python manual. As this is the native cplex representation of your model.

[Romain Montagné]

Ok thanks.

prob.solution.MIP.get_best_objective() does the trick if any one else wonders.