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dc.contributor.authorWegener, Ingode
dc.date.accessioned2004-12-07T08:20:42Z-
dc.date.available2004-12-07T08:20:42Z-
dc.date.created2001de
dc.date.issued2001-10-29de
dc.identifier.urihttp://hdl.handle.net/2003/5403-
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-15285-
dc.description.abstractMutation and crossov r are th main s arch op rators of different variants of evolutionary algorithms. Despite the many discussions on the importance of crossover nobody has proved rigorously for some explicitly defined fitness functions fn : {0 , 1 }n -> R that a genetic algorithm with crossover (but without idealization)can optimize fn in expected polynomial time while all volution strategies based only on mutation (and selection) need expected exponential time. Here such functions and proofs are presented. For some functions one-point crossover is appropriate while for others uniform crossover is the right choice.en
dc.format.extent152314 bytes-
dc.format.extent301722 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypeapplication/postscript-
dc.language.isoende
dc.publisherUniversität Dortmundde
dc.relation.ispartofseriesReihe Computational Intelligence ; 104de
dc.subject.ddc004de
dc.titleReal Royal Road Functions - Where Crossover Provably is Essentialen
dc.typeTextde
dc.type.publicationtypereport-
dcterms.accessRightsopen access-
Appears in Collections:Sonderforschungsbereich (SFB) 531

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