Op 22-08-12 03:47, Davide Sottara schreef:
Choco is written in java and has a very permissive license model,
unlike the
others which are either
commercial or GPLx, but the last time I tried it ( ~6 months ago ) it was
still suffering from some numerical computation problems. I had it almost
stuck in a local plateau for several seconds while
trying to solve a small minimization problem with ~4 variables and ~10
constraints.
For such a small problem you might be better of using brute force (which
usually works up to n <= 10).
Most solvers don't scale, so any experiment done on a small dataset
tells you nothing about how they behave on big datasets :(
For example, LocalSolver (the only real competition for Drools Planner),
can't handle the roadef B9 instance with 50 000 variables yet with 40GB
of RAM as a whole:
http://www.localsolver.com/news.html?id=11
Planner can handle it as a whole with only 1GB of RAM and has better
results:
http://blog.athico.com/2012/06/roadef-2012-first-results-for-dataset-b.html
@Geoffrey: but can Planner be used effectively - i.e. with little overhead -
for LP optimization problems,
including the integer-LP and the mixed-LP variants? And quadratic ones?
Yes, but Planner doesn't use LP, it uses Metaheuristics. Both have their
uses.
Metaheuristics and LP can both be applied to planning, scheduling and
assignment problems, but in my experience (shown by the competitions),
metaheuristics clearly win most battles, especially if the problems
scales out.
LP is usually better for non-discrete (often non NP-complete) problems,
such as figuring out the center of a triangle.
LP is also far less powerful on how to define the constraints.
For example getting LP to solve a toy problem like TSP requires complex
equations (such as comb inequalities) to squeeze the hard constraints
into equations. Metaheuristics just repair the chain while doing moves.
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