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A particle swarm solution based on lexicographical goal programming for a multiobjective fuzzy open shop problem

dc.contributor.authorPalacios Alonso, Juan José 
dc.contributor.authorGonzález Rodríguez, Inés 
dc.contributor.authorRodríguez Vela, María del Camino 
dc.contributor.authorPuente Peinador, Jorge 
dc.date.accessioned2015-07-13T11:28:49Z
dc.date.available2015-07-13T11:28:49Z
dc.date.issued2015
dc.identifier.citationAI Communications, 28(2), p. 239-257 (2015); doi:10.3233/AIC-140637
dc.identifier.issn0921-7126
dc.identifier.issn1875-8452
dc.identifier.urihttp://hdl.handle.net/10651/31632
dc.description.abstractIn the sequel, we consider a multiobjective open shop scheduling problem with uncertain durations modelled as fuzzy numbers. Given crisp due dates, the objective is to minimise both the makespan and the maximum tardiness. We formulate the multiobjective problem as a fuzzy goal programming model based on lexicographical minimisation of expected values. The resulting problem is solved using a particle swarm optimization approach searching in the space of possibly active schedules. Experimental results are presented on several problem instances to evaluate the proposed method, illustrating its potential
dc.description.sponsorshipSpanish Government [FEDER TIN2010-20976-C0202, MTM2010-16051]
dc.format.extentp. 239-257
dc.language.isoeng
dc.publisherIOS Press
dc.relation.ispartofAI Communications, 28(2)
dc.rightsCC Reconocimiento - No comercial - Sin obras derivadas 4.0 Internacional
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.source.urihttp://content.iospress.com/articles/ai-communications/aic637
dc.titleA particle swarm solution based on lexicographical goal programming for a multiobjective fuzzy open shop problemeng
dc.typejournal article
dc.identifier.doi10.3233/AIC-140637
dc.relation.projectIDMEC-FEDER/TIN2010-20976-C0202
dc.relation.projectIDMEC-FEDER/MTM2010-16051
dc.relation.publisherversionhttp://dx.doi.org/10.3233/AIC-140637
dc.rights.accessRightsopen access
dc.type.hasVersionAM


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CC Reconocimiento - No comercial - Sin obras derivadas 4.0 Internacional
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