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https://issues.apache.org/jira/browse/MATH-442?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12932936#action_12932936
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Dr. Dietmar Wolz commented on MATH-442:
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http://cm.bell-labs.com/cm/cs/doc/96/4-02.ps.gz states that a method should not
'in its heart' develop an approximate gradient as for instance quasi-Newton
methods. I don't think this qualifies CMA-ES as 'direct' method. "Adaptation of
the covariance matrix amounts to learning a second order model of the
underlying objective function similar to the approximation of the inverse
Hessian matrix in the Quasi-Newton method in classical optimization ".
> 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
> 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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