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A comparative study of evolutionary optimization techniques in dynamic environments

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dc.contributor.authorsAyvaz, Demet; Topcuoglu, Haluk; Gurgen, Fikret
dc.contributor.editorKeijzer, M
dc.date.accessioned2022-03-12T15:59:15Z
dc.date.accessioned2026-01-11T11:06:55Z
dc.date.available2022-03-12T15:59:15Z
dc.date.issued2006
dc.description.abstractGenetic Algorithms have widely been used for solving optimization problems in stationary environments. In recent years, there has been a growing interest for investigating and improving the performance of these algorithms in dynamic environments where the fitness landscape changes. In this study, we present an extensive comparison of several algorithms with different characteristics on a common platform by using the moving peaks benchmark and by varying problem parameters.
dc.identifier.doidoiWOS:000249917300192
dc.identifier.isbn978-1-59593-186-3
dc.identifier.urihttps://hdl.handle.net/11424/224346
dc.identifier.wosWOS:000249917300192
dc.language.isoeng
dc.publisherASSOC COMPUTING MACHINERY
dc.relation.ispartofGECCO 2006: GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE, VOL 1 AND 2
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectgenetic algorithms
dc.subjectdynamic environments
dc.subjectmultimodal optimization
dc.subjectperformance evaluation
dc.titleA comparative study of evolutionary optimization techniques in dynamic environments
dc.typeconferenceObject
dspace.entity.typePublication
oaire.citation.endPage+
oaire.citation.startPage1397
oaire.citation.titleGECCO 2006: GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE, VOL 1 AND 2

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