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dc.contributor.authorRudolph, Günterde
dc.date.accessioned2004-12-07T08:20:04Z-
dc.date.available2004-12-07T08:20:04Z-
dc.date.created1999de
dc.date.issued2001-10-16de
dc.identifier.urihttp://hdl.handle.net/2003/5372-
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-15257-
dc.description.abstractThe search for minimal elements in partially ordered sets is a generalization of the task of finding Pareto-optimal elements in multi-criteria optimization problems. Since there are usually many minimal elements within a partially ordered set, a population-based evolutionary search is, as a matter of principle, capable of finding several minimal elements simultaneously and gains therefore a steadily increase of popularity. Here, we present an evolutionary algorithm which population converges with probability one to the set of minimal elements within a finite number of iterations.en
dc.format.extent67766 bytes-
dc.format.extent77644 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypeapplication/postscript-
dc.language.isoende
dc.publisherUniversität Dortmundde
dc.relation.ispartofseriesReihe Computational Intelligence ; 67de
dc.subject.ddc004de
dc.titleEvolutionary Search under Partially Ordered Fitness Setsen
dc.typeTextde
dc.type.publicationtypereport-
dcterms.accessRightsopen access-
Appears in Collections:Sonderforschungsbereich (SFB) 531

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