Local Convergence Rates of Simple Evolutionary Algorithms with Cauchy Mutations

dc.contributor.authorRudolph, Günterde
dc.contributor.authorRudoph, Günterde
dc.date.accessioned2004-12-07T08:19:27Z
dc.date.available2004-12-07T08:19:27Z
dc.date.created1998de
dc.date.issued1998-11-08de
dc.description.abstractThe standard choice for mutating an individual of an evolutionary algorithm with continuous variables is the normal distribution; however other distributions, especially some versions of the multivariate Cauchy distribution, have recently gained increased popularity in practical applications. Here the extent to which Cauchy mutation distributions may affect the local convergence behavior of evolutionary algorithms is analyzed. The results show that the order of local convergence is identical for Gaussian and spherical Cauchy distributions, whereas nonspherical Cauchy mutations lead to slower local convergence. As a by-product of the analysis some recommendations for the parametrization of the self-adaptive step size control mechanism can be derived.en
dc.format.extent322238 bytes
dc.format.extent434048 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypeapplication/postscript
dc.identifier.urihttp://hdl.handle.net/2003/5337
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-15270
dc.language.isoende
dc.publisherUniversität Dortmundde
dc.relation.ispartofseriesReihe Computational Intelligence ; 37de
dc.subject.ddc004de
dc.titleLocal Convergence Rates of Simple Evolutionary Algorithms with Cauchy Mutationsen
dc.typeTextde
dc.type.publicationtypereport
dcterms.accessRightsopen access

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