[rules-users] DROOLS PLANNER - computation times and comparison

[ge0ffrey]

KD wrote:
> 
> I went through some presentations on bin packing/cloud balance problems.
> I am interested in knowing about computational results relating to these
> problems, specially related to the size of the instances tackled and
> computational times. So how well do the methods scale with problem size?
> 

They scale very good, both in data and in constraints.
In my experience, local search (tabu search, SA, ...) is the best up-scaling
algorithm out there.
Getting StartingSolutionInitializer right and setting a
minimalAcceptedSelection so a step is done every 1-2 seconds is critical
though.

Join the webinar next week:
  http://blog.athico.com/2011/05/drools-planner-webinar-on-wednesday.html
If I have time I 'll include some graphs to prove how it scales out.
Or try it yourself in the examples: run the *Importer (classes with main())
and they 'll output you how big each dataset it. Then use the *Benchmarker
to get a graph which the results for each dataset.


KD wrote:
> 
> Could you also comment on performance/computational times with other
> commercial solvers?
> 
Publishing benchmarks of some of the commercial solvers is illegal under
their license terms.
Some notes:
- Micro benchmarks are generally worthless and cheatable (see JavaOne/Devoxx
presentations of Cliff Click, Joshua Bloch, ...).
- Benchmarking N-queens is stupid: it's not NP complete. It's very cheatable
and besides the Drools Planner implementation is an unoptimized tutorial.
- Benchmarking pure TSP is ok but short-sighted. You need to be able to
scale in data AND constraints. (I am working on a TSP example in Planner but
it's not finished yet).
- Competitions such as ITC2007, RAS, ... are great benchmarks: they use
real-world data, real constraints, ... 
I finished 4th in ITC2007 track 1 (much has improved since then) and all of
the other finalists were researchers that wrote their experimental solvers
from scratch as far as I know.

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