I use several "flavors" of evolutionary optimization: particle swarm and variations of the genetic algorithm. Using latin hypercube sampling to generate the initial population is highly recommended. There are several online websites and you can even find some algorithms coded in python. Don't forget to use swig or f2py when you can. On Thu, Aug 28, 2008 at 10:23 AM, bryan cole <bryan.cole@teraview.com> wrote:
Hi,
I'll looking for a bit of guidance as to what sort of algorithm is most appropriate/efficient for finding the local maximum of a function (in 2 dimensions), where each function evaluation is 1) noisy and 2) expensive/slow to evaluate.
I'd welcome any suggestions for where best to start investigating this (text books, references, web-sites or existing optimisation libraries). I've no background in this field at all.
cheers, Bryan
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