[SCIP] SCIP speed-up for .LP files

[Ambros Gleixner]

Hi Marcus,

28456 variables are in general not particularly large, but for hard 
problems, also medium-sized instances can become very difficult.

Gurobi is known to be stronger than SCIP, but it could be that with the 
right parameters also SCIP can solve the instances.  As a starter try to 
change emphasis settings, one or more of

set presolving emphasis aggressive
set separating emphasis {off,fast,aggressive}
set heuristics emphasis aggressive
set emphasis {feasibility,optimality,hardlp}

and/or look at the statistics via "display statistics" to find expensive 
and unsuccessful plugins to be deactivated.

But giving more detailed advice here is difficult without seeing the 
instance.  You can send me a larger, problematic instance of your model 
as a personal message, and I will try to find the time to look at it.

Best,
Ambros





Am 14.06.2018 um 23:21 schrieb Marcus Garvie:
> Hi everyone,
> 
> this is my first post, so please understand that my knowledge of SCIP is 
> low!
> 
> I have been solving some large binary linear programming problems with 
> no objective function. I solve .LP files using a terminal to issue the 
> commands on my Mac. The .LP files are automatically generated, with e.g. 
> the attached format.
> 
> The only commands I issue are
> 
> SCIP> read test.lp
> SCIP> optimize test.lp
> 
> The problem is that for very large problems (e.g. 28456 variables) the 
> solver seems to be running forever (> 2 days)! I tried the same problem 
> in Gurobi and it gave me the correct solution in 15 minutes. (I’m 
> wanting to use SCIP because it has some easy options for giving me all 
> feasible solutions, while Gurobi does not).
> 
> I also tried the problem in CPLEX, but it has some limitations on the 
> length of the variable names (Error  1464) so I’m a little stuck if I 
> want multiple solutions for large problems.
> 
> Any advice would be appreciated.
> 
> Marcus.
> 
> PS I only know how to problems in the  .LP format!
> 
> 
> 
> ________________________________
> Marcus R Garvie
> Associate Professor
> Rm 552 MacNaughton Bldg
> Dept. of Math & Stats
> University of Guelph
> Guelph, ON Canada N1G 2W1
> Tel. 519-824-4120 ext 53409
> Email. _mgarvie at uoguelph.ca_ <mailto:mgarvie at uoguelph.ca>
> 
> 
> 
> 
> 
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-- 
Ambros Gleixner, Research Group Mathematical Optimization Methods at 
Zuse Institute Berlin, http://www.zib.de/gleixner