[SciPy-dev] Advice on Simulated Annealing (ticket #875)
Mon Mar 2 11:04:13 CST 2009
Here is code that will demonstrate the failure. Suppose you want to
minimize the simple function f(x,y)=x^2+y^2, but you want to do it in a
specified domain. This will not respect the upper and lower bounds:
import numpy as N
import scipy.optimize.anneal as anneal
On Mon, Mar 2, 2009 at 9:43 AM, william ratcliff <firstname.lastname@example.org
> I posted a suggested patch because it would seem that the simulated
> annealing routine in scipy as it was would not respect bounds for the search
> space. I'll try to reconstruct the test case to show where it fails. There
> seemed to be a lack of interest in a version that did respect bounds
> (upper/lower limits on the parameters), so I've just been using my own copy.
> On Mon, Mar 2, 2009 at 8:54 AM, Sturla Molden <email@example.com> wrote:
>> On 3/2/2009 6:55 AM, Stéfan van der Walt wrote:
>> > http://scipy.org/scipy/scipy/ticket/875#comment:1
>> > looks fragile, but I don't know how to fix it best.
>> This ticket i bogus. There is no simple_sa in anneal.py in SVN, and line
>> 151 is a docstring. Google says that the simple_sa class was posted to
>> this mailing list two years ago by William Ratcliff. But as far as I can
>> tell it is not in SciPy.
>> Sturla Molden
>> Scipy-dev mailing list
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