Re: Intelligent ways to search parameter space?

[Steve Shervais]

Steve,
Must be an idea whose time has come. I used GA optimization to search
parameter space in an inventory control problem for my dissertation --
"in press" as they say. The goal was not so much optimization of any
parameter as characterization of the search space.  The idea was that a
GA would spend more time near the "hilltops". These are areas where you
want your controller to really understand the problem in detail. The GA
will spend proportionally less time in the "flats", where what you need
to know is how to find the nearest hill. Turns out, on the problem I
addressed, there was no difference between random, grid-stepping, and GA
parameter selection, but that might just be the fault of my specific
problem (very spiky, deceptive landscape).

Steve Shervais
Assistant Professor, MIS
Eastern Washington University
address@hidden

"Stephen C. Upton" wrote:
> 
> As somewhat of an aside, I am also finishing up a software framework for
> using Natural Algorithms (GA's, simulated annealing, ant algorithms,
> cultural algorithms) to "search" over simulation spaces. (this is part
> of my long overdue dissertation).  The basic idea is to formulate your
> search as an optimization problem and then use the Natural Algorithms as
> heuristics to find the "minimum" or the set of minimum.  This is the


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