[SciPy-user] Simulated annealing in scipy

Robert Kern rkern at ucsd.edu
Fri Jul 22 07:44:06 CDT 2005

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.

Robert Kern
rkern at ucsd.edu

"In the fields of hell where the grass grows high
  Are the graves of dreams allowed to die."
   -- Richard Harter

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