We recently ran a multiobjective EA using MASON for one of the objective
values. Each experiment took rouhgtly 100 hours of CPU time, and there
were a total of 10 experiments.
On Wed, 1 Dec 2004, Liviu Panait wrote:
> I have similar issues. Not to mention that you only get one run done,
> so no statistical significance.
> Things you may want to try:
> - decrease the population size
> - start with a smaller number of evaluations (say 5) to discriminate
> among good and bad individuals; increase the number of evaluations
> later on during the run to discriminate among really good individuals.
> (check out Grajdeanu and DeJong paper in Late Breaking Papers of
> - try using an island model with N islands and 500/N individuals in
> each island
> - try distribute evaluations to several computers (I am not sure what
> the status of that code is, but there is some code for this stuff
> that's being brushed up by one of Sean Luke's students).
> - be patient
> On Dec 1, 2004, at 11:55 AM, Steve Butcher wrote:
> > Dear all,
> > I'm currently using GP to search the solution space of a problem in
> > pursuit and evasion.
> > Using MASON as a simulator and ECJ as the GP package, I've come up with
> > a system that does one simulation in approximately 4 seconds. As there
> > are 20 trials per evaluation, 500 individuals and 51 generations. This
> > comes out to approximately 23 days of computing time. Well, assuming
> > there is to be a write-up of results and a prepared presentation, this
> > put me about 18 days over what I had available so I took some
> > shortcuts.
> > However, I'm wondering informally if anyone on the list has tackled
> > problems with similar run times.
> > Cordially,
> > Steve