[SciPy-Dev] optimize - add algorithm for global optimization: GenSA

[Jacob Stevenson]

In my opinion a robust implementation of a simulated annealing based
optimizer would be welcome.  There are cases when this would be preferable
to basinhopping, e.g. when non-smooth or non-continuous functions make the
local optimization step in basinhopping less effective.

I think the first step is to make a pull request (or send a link if you
already did) where we can review the code and have discussions.

Best,
Jake

On Fri, 23 Oct 2015 at 14:10 Gubian, Sylvain <Sylvain.Gubian at pmi.com> wrote:

> Hi everyone,
>
> We would like to propose a new method, GenSA,  for global optimization to
> be included in the optimize module.
>
> GenSA is an implementation of the General Simulated Annealing algorithm
> (GSA, http://www.sciencedirect.com/science/article/pii/S0378437196002713).
> This approach generalizes CSA (Classical Simulated Annealing) and FSA (Fast
> Simulated Annealing) to search for the global minimum more efficiently. The
> algorithm is explained in more detail in this reference:
> http://journal.r-project.org/archive/2013-1/xiang-gubian-suomela-etal.pdf.
>
> SciPy has already in the past included a method based on simulated
> annealing, called anneal, which has been deprecated in 0.14 (with an advice
> to use basinhopping) and eventually removed in 0.16.
>
> A previously published comparison of 18 optimization methods in the R
> language (http://www.jstatsoft.org/v60/i06/paper) shows that GenSA is,
> among the methods tested, one of the “most capable of consistently
> returning a solution near the global minimum of each test function”. This
> paper however did not consider basinhopping, so we have performed some
> tests which tend to show that GenSA is more efficient than basinhopping
> for high dimension problems. The results have been presented in a poster in
> PyCon UK 2015 (Coventry).
>
> The code is ready and passes unit tests and PEP8. We hope it would be a
> useful addition to SciPy and would be happy to have your opinion.
>
> Thanks,
>
> Sylvain.
> _______________________________________________
> SciPy-Dev mailing list
> SciPy-Dev at scipy.org
> https://mail.scipy.org/mailman/listinfo/scipy-dev
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.python.org/pipermail/scipy-dev/attachments/20151023/b36b1129/attachment.html>