[SciPy-Dev] Consideration of differential evolution minimizer being added to scipy.optimize.

[Andrea Gavana]

Hi

On Tuesday, March 4, 2014, Petr Baudis wrote:

>   Hi!
>
> On Tue, Mar 04, 2014 at 09:42:36PM +0100, Ralf Gommers wrote:
> > Andrea Gavana has posted a nice set of benchmarks before:
> > http://article.gmane.org/gmane.comp.python.scientific.devel/18383, you
> > could contact him to add your algorithm (or do a similar comparison
> > yourself). Seeing your code in a comparison like
> > http://infinity77.net/global_optimization/multidimensional.html would be
> > useful.
>
>   Another interesting benchmark might be the COCO benchmark of BBOB
> workshops which is often used in academia for global optimization
> performance comparisons:
>
>         http://coco.gforge.inria.fr/doku.php
>
> Though it focuses on black-box optimization.  I plan to publish a
> performance graph for all SciPy's optimizers wrapped in basinhopping
> as benchmarked within COCO after the end of March (a month of deadlines
> for me), if noone beats me to it.
>
>   (My long-term work focuses on online portfolio algorithms, i.e. such
> that can dynamically switch between minimization methods based on their
> performance so far when optimizing the function.  My hope is to
> eventually find some that could be beneficial enough to be worth
> including in SciPy.  A work-in-progress framework I'm using so far is
> https://github.com/pasky/cocopf )
>
> > Another question is if we think this is in scope for scipy.optimize,
> given
> > that PyGMO has this same algorithm and a number of similar ones.
>
>   I know that as SciPy user, I would appreciate having at least a single
> reference, high-performance population-based algorithm in scipy.optimize.
> Whether to go with the contributed DE code or use some more
> sophisticated approach to choose a suitable one (I believe the top
> state-of-art are the CMA-ES variants?), I don't know.
>
>                                 Petr "Pasky" Baudis
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