[SciPy-user] Simulated annealing in scipy

[Robert Kern]

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