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How to stop a MILP before it reaches the optimal solution (using different backends)?

asked 2015-02-24 03:19:05 -0500

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Sometimes you don't need an optimal solution. A feasible solution is a must, but a decent value of the objective function will do. At least that's better than waiting forever...

Some backends (most?, all?) for the MixedIntegerLinearProgram support different stop criteria. But it took me quite some time to find them. How to tell MixedIntegerLinearProgram not to continue until the optimal solution is found?

PD: I found the answer (at least part of it) before I submitted this question, but I think it's good to ask the question for reference:

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answered 2015-02-24 03:20:04 -0500

pang gravatar image

For the GLPK backend, you pass an extra, backend-specific parameter to the solver:

P = MixedIntegerLinearProgram(solver = "GLPK")
P.solver_parameter("timelimit", timelimit)
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Asked: 2015-02-24 03:19:05 -0500

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Last updated: Feb 24 '15