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dc.contributor.authorDavendra, Donald David
dc.contributor.authorZelinka, Ivan
dc.contributor.authorBialic-Davendra, Magdalena
dc.contributor.authorŠenkeřík, Roman
dc.contributor.authorJašek, Roman
dc.date.accessioned2012-12-03T12:05:36Z
dc.date.available2012-12-03T12:05:36Z
dc.date.issued2012
dc.identifier.citationCentral European Journal of Operations Research. 2012, vol. 20, issue 4, s. 679-717.cs
dc.identifier.issn1435-246X
dc.identifier.issn1613-9178
dc.identifier.urihttp://hdl.handle.net/10084/95776
dc.description.abstractA novel clustered population paradigm is presented in this paper which is based on Chaos principles of edges and attractors. Convergence in evolutionary algorithms is viewed as a manifestation through cyclic dynamics and thus a new population is developed which is clustered and separated through new segregation bias rules. This population is embedded on the Enhanced Differential Evolution and the flow shop scheduling problem with blocking is solved. The two flow shop benchmark problems of Rec/Car/Hel and Taillard are solved with this new approach and the results favorably compared with published results in literature. A total of 49 new upper bounds for the Taillard problems was obtained during experimentation.cs
dc.language.isoencs
dc.publisherSpringercs
dc.relation.ispartofseriesCentral European Journal of Operations Researchcs
dc.relation.urihttp://dx.doi.org/10.1007/s10100-011-0198-3cs
dc.subjectdifferential evolutioncs
dc.subjectflow shop scheduling with blockingcs
dc.subjectschedulingcs
dc.subjectevolutionary algorithmscs
dc.titleClustered enhanced differential evolution for the blocking flow shop scheduling problemcs
dc.typearticlecs
dc.identifier.locationNení ve fondu ÚKcs
dc.identifier.doi10.1007/s10100-011-0198-3
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.volume20cs
dc.description.issue4cs
dc.description.lastpage717cs
dc.description.firstpage679cs
dc.identifier.wos000310229300006


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