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[Help-glpk] Using a heuristic to find a first integer solution quickly

From: Andrea Curtoni
Subject: [Help-glpk] Using a heuristic to find a first integer solution quickly
Date: Tue, 19 Nov 2002 19:13:46 +0100
User-agent: Mozilla/5.0 (X11; U; Linux i686; en-US; rv:1.0.0) Gecko/20020623 Debian/1.0.0-0.woody.1

I found on the net this message:

On Tue, 15 Oct 2002, Dai, Jianrong wrote:

Hi, everyone,

I need to solve a MILP problem with hundreds of binary variables. Because
GLPK runs too slow (already 4 days, still running), I'm thinking about using
a optimal solution of an heuristic method to speed up the optimization
process. I'm wondering whether it is possible to do so. If the answer is
yes, please show me how to do it. Thanks.


It should be possible. One (not very good way) might be to use the
"objective value" from the heuristic method and modify the source of the
branch and bound solver so that it is possible to specify a "cut" cost
(eg. set the variable bb->best (?) to the objective value from the
heuristic method. This should make the bb solver to skip all branches
that is more "expansive" than the heuristic solution.


I have a similar problem, GLPK takes too much time to find the first integer 
feasible solution, but i have a heuristic able to find a sub-optimal integer 
feasible solution in a short time.
How can I use it?
Isn't there a simpler method than changing the source of the branch and bound 

Thanks in advance,

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