[SciPy-user] Simulated annealing in scipy
nwagner at mecha.uni-stuttgart.de
Fri Jul 22 07:48:47 CDT 2005
Robert Kern wrote:
> Nils Wagner wrote:
>> Hi all,
>> I tried to find the smallest eigenvalue of a generalized
>> eigenvalue problem
>> K x = \lambda M x
>> by minimizing the Rayleigh quotient
>> R = x^T K x / x^T M x
>> where K and M are symmetric positive definite.
>> I have used optimize.anneal for this purpose (annealing.py for details).
>> However, the simulated annealing algorithm doesn't terminate with the
>> global optimal solution.
>> But for what reason ?
> Simulated annealing isn't perfect. It has quite a number of tweakable
> parameters. Finding the right values for those is something of an art.
Do you think that genetic algorithms are an option for my task ?
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