PuLP very slow when adding many constraints

问题:

I'm trying to use PuLP, but it is taking 50 seconds to add 4000 constraints (with 67 variables). Solving the problem only takes a fraction of a second.

We want to use PuLP to easily test several solvers on a large set of problems.

Should it be taking PuLP this long? Using PyGLPK directly takes only a fraction of second including both setup and solving, so I hope not. What can I do to improve the efficiency of this step in PuLP?

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Update

My constraints matrix is very sparse, and I was able to reduce the setup time to 4 or 5 seconds for this particular problem by only including nonzero coefficients. I am still able to write my own .lp or .mps formatted file, solve the problem with a cbc or glpsol subprocess, and parse the solution much more efficiently than PuLP, simply because I can write the input file in a few ms when PuLP takes several seconds. I'm still not sure why this would be.

回答1:

I don't have reps enough to comment.

But have you looked at this:

https://groups.google.com/forum/#!topic/pulp-or-discuss/p1N2fkVtYyM

The question is asked:

"The problem is solved in less than 0.5 second.
However setting it up with PULP takes more than 10 seconds. "

This seems to be what you report as well. And the solution is to not use += or sum(...) operators, but instead, as explained in the link as well:

yeah using the += operator with pulp is really slow, as is using sum() 
instead of lpSum()

So maybe you are adding the constraints 1 at a time to PuLP instead of building the list of constraints first and then, at the end, add the constraints to PuLP?