[SciPy-user] advice on stochastic(?) optimisation

[Kimberly Artita]

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 at 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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-- 
Kimberly S. Artita
Graduate Student, Engineering Science
College of Engineering
Southern Illinois University Carbondale
Carbondale, Illinois 62901-6603
Office: ENGB 0044, Water Resources Research Lab
Phone: (618)-528-0349
E-mail: kartita at gmail.com, kartita at siu.edu
web: http://civil.engr.siu.edu/GraduateStudents/artita/index.html