On the Effects of Outliers on Evolutionary Optimization

dc.contributor.author	Arnold, Dirk V.	de
dc.contributor.author	Beyer, Hans-Georg	de
dc.date.accessioned	2004-12-07T08:21:23Z
dc.date.available	2004-12-07T08:21:23Z
dc.date.created	2003	de
dc.date.issued	2003-12-23	de
dc.description.abstract	Most studies concerned with the effects of noise on evolutionary computation have assumed a Gaussian noise model. However, practical optimization strategies frequently face situations where the noise is not Gaussian, and sometimes it does not even have a nite variance.In particular, outliers may be present. In this paper, Cauchy distributed noise is used for modeling such situations. A performance law that describes how the progress of an evolution strategy using intermediate recombination scales in the presence of such noise is derived. Implications of that law are studied numerically, and comparisons with the case of Gaussian noise are drawn.	en
dc.format.extent	215021 bytes
dc.format.extent	250009 bytes
dc.format.mimetype	application/pdf
dc.format.mimetype	application/postscript
dc.identifier.uri	http://hdl.handle.net/2003/5434
dc.identifier.uri	http://dx.doi.org/10.17877/DE290R-15352
dc.language.iso	en	de
dc.publisher	Universität Dortmund	de
dc.relation.ispartofseries	Reihe Computational Intelligence ; 144	de
dc.subject.ddc	004	de
dc.title	On the Effects of Outliers on Evolutionary Optimization	en
dc.type	Text	de
dc.type.publicationtype	report
dcterms.accessRights	open access

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