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Re: [Fwd: Feeding an initial feasible solution to GLPK for MILP in CVXP

From: Michael Hennebry
Subject: Re: [Fwd: Feeding an initial feasible solution to GLPK for MILP in CVXPy]
Date: Fri, 10 Sep 2021 11:27:08 -0500 (CDT)
User-agent: Alpine 2.20 (DEB 67 2015-01-07)

On Thu, 9 Sep 2021, Andrew Makhorin quoted "Vasebi, Saeed [JJCUS]" 

I have a MILP problem in GLPK, using CVXPy library. GLPK quickly finds
a primary solution (optimal but not integer). But when GLPK switches
to branch-and-cut to find an optimal integer solution, it moves very
slowly. The main reason is
 that GLPK does not find any feasible integer solution after many
iterations (see the below log). I can use a simple heuristic algorithm
to find an initial feasible and integer solution, which can help GLPK
to quickly eliminate non-optimal branches. I am wondering
 if there is any way to feed this initial feasible integer solution to
GLPK, or its objective value?  

It's clunky, but I think it can be done with the GLP_IHEUR callback.
Failing that, I think that you can just add a constraint.

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