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I think with those solve times you will be better off trying to avoid the disk writes, maybe a ramdisk?Stu
Stuart MitchellPhD Engineering ScienceExtraordinary Freelance Programmer and Optimisation Guru
On Thu, Mar 15, 2018 at 4:41 PM, Clay Campaigne <clay.ca...@gmail.com> wrote:
Hans Mittelmann's list of benchmarks for MILP solution times is a standard place to look. CBC is generally the fastest free solver, but the proprietary ones (I'm thinking Gurobi and CPLEX) are generally 20-30x faster. SCIP semi-proprietary and its performance is halfway in between (geometrically). You can use Gurobi for free if it's academic, SCIP for free if it's non-commercial (case-by-case by contacting the developers), and a SCIP license costs I think $1000 perpetual, for commercial purposes. Subject to negotiation depending on the application and pricing model of any resulting product. Gurobi has transparent pricing, and I think CPLEX requires contacting them and maybe negotiation.MILP benchmarks:I've used CBC, Gurobi, CPLEX, and SCIP, and my experience roughtly lines up with this, except in certaint MIP that more closely resempled combinatorial optimization, where SCIP was pretty close to CBC.bestClay
On Wed, Mar 14, 2018 at 3:47 PM, Nicholas Gorman <n.gor...@gmail.com> wrote:
Hi Folks,I am using Pulp to solver some problems that include a mix of binary variables and linear variables. Typically these take between 2 and 5 s to solve and this has become the main bottle neck in my program. So far I have just used the default PULP_CBC_CMD solver, but wanted to explore using other solvers to speed up the program. I was wondering if someone had some tips on how to approach this or could point me in the direction of some resource that explained when to use which types of solvers and why.Kind Regards,Nick
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--Clay CampaigneCell Phone: (773) 732-9406
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https://github.com/coin-or/pulp/blob/bac6d9d2214ba773d638d2de5149940cfd711359/src/pulp/solvers.py#L1558
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https://github.com/coin-or/pulp/blob/bac6d9d2214ba773d638d2de5149940cfd711359/src/pulp/solvers.py#L1426
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