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Flow shop scheduling using clustered differential evolution

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dc.title Flow shop scheduling using clustered differential evolution en
dc.contributor.author Davendra, Donald David
dc.contributor.author Zelinka, Ivan
dc.contributor.author Onwubolu, Godfrey
dc.relation.ispartof 23rd European Conference on Modelling and Simulation (ECMS 2009)
dc.identifier.isbn 978-0-9553018-8-9
dc.date.issued 2009
dc.citation.spage 70
dc.citation.epage 76
dc.event.title 23rd European Conference on Modelling and Simulation (ECMS)
dc.event.location Madrid
utb.event.state-en Spain
utb.event.state-cs Španělsko
dc.event.sdate 2009-06-09
dc.event.edate 2009-06-12
dc.type conferenceObject
dc.language.iso en
dc.publisher European Council for Modelling and Simulation (ECMS) en
dc.relation.uri http://www.scs-europe.net/conf/ecms2009/ecms2009%20CD/ecms2009%20accepted%20papers/is_0028_bce3df7d.pdf
dc.subject Differential evolution en
dc.subject flow shop scheduling en
dc.subject clustering en
dc.description.abstract A generic approach of population dynamics and clustering for permutative problems is presented in this paper. Diversity indicators are created from solution ordering and its mapping is shown as an advantage for population control in metaheuristics. Differential Evolution Algorithm is embedded with a population based on this approach and vetted with the Flow shop scheduling problem. Extensive experimentation is conducted on benchmark problems in this area with good results. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1002792
utb.identifier.rivid RIV/70883521:28140/09:63510075!RIV11-MSM-28140___
utb.identifier.obdid 43861054
utb.identifier.scopus 2-s2.0-84857722324
utb.identifier.wok 000302016000011
utb.source d-wok
dc.date.accessioned 2012-06-04T11:34:08Z
dc.date.available 2012-06-04T11:34:08Z
utb.contributor.internalauthor Davendra, Donald David
utb.contributor.internalauthor Zelinka, Ivan
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