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From "Luc Maisonobe (JIRA)" <j...@apache.org>
Subject [jira] Commented: (MATH-442) CMA evolution strategy is missing in optimization
Date Fri, 04 Feb 2011 19:44:30 GMT

    [ https://issues.apache.org/jira/browse/MATH-442?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12990698#comment-12990698
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Luc Maisonobe commented on MATH-442:
------------------------------------

As the code is rather large and it was already developed outside of the Apache foundation
and used (for GTOC at least), I think that in addition to the ICLA we need a software grant.
The ICLA is for the contributors future work on the component (fixing bugs, improving the
code ...) but the grant is for the initial code to be imported.
Thanks for this contribution

> CMA evolution strategy is missing in optimization
> -------------------------------------------------
>
>                 Key: MATH-442
>                 URL: https://issues.apache.org/jira/browse/MATH-442
>             Project: Commons Math
>          Issue Type: New Feature
>    Affects Versions: 3.0
>            Reporter: Dr. Dietmar Wolz
>             Fix For: 3.0
>
>         Attachments: cmaes.math.patch
>
>   Original Estimate: 48h
>  Remaining Estimate: 48h
>
> Recently I implemented the optimization algorithm CMA-ES based on org.apache.commons.math.linear
and used it for the GTOC5 global trajectory optimization contest http://gtoc5.math.msu.su/.
It implements the MultivariateRealOptimizer interface and would nicely fit into the org.apache.commons.math.optimization
package. The original author of CMA-ES (Nikolaus Hansen) volunteered to support me (proof-reading
+ testing) in the creation of a CMA-ES contribution for commons.math. 
> The CMA evolution strategy http://www.lri.fr/~hansen/cmaesintro.html is a very powerful
algorithm for difficult non-linear non-convex optimization problems in continuous domain.
See http://www.lri.fr/~hansen/cec2005.html for a comparison chart. If there is interest I
will create a patch including the proposed Implementation for evaluation. It seems we would
need an additional sub-package - org.apache.commons.math.optimization.evolutionary.

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