
From:  Andrea Curtoni 
Subject:  [Helpglpk] Using a heuristic to find a first integer solution quickly 
Date:  Tue, 19 Nov 2002 19:13:46 +0100 
Useragent:  Mozilla/5.0 (X11; U; Linux i686; enUS; rv:1.0.0) Gecko/20020623 Debian/1.0.00.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. JianrongIt 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. /Niklas
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 suboptimal 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 solver? Thanks in advance, Andrea
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