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A genetic solution based on lexicographical goal programming for a multiobjective job shop with uncertainty

dc.contributor.authorGonzález Rodríguez, Inés 
dc.contributor.authorRodríguez Vela, María del Camino 
dc.contributor.authorPuente Peinador, Jorge 
dc.date.accessioned2013-01-30T09:57:12Z
dc.date.available2013-01-30T09:57:12Z
dc.date.issued2010
dc.identifier.citationJournal of Intelligent Manufacturing, 21(1), p. 65-73 (2010); doi:10.1007/s10845-008-0161-xspa
dc.identifier.issn0956-5515
dc.identifier.urihttp://hdl.handle.net/10651/6167
dc.description.abstractIn this work we consider a multiobjective job shop problem with uncertain durations and crisp due dates. Ill-known durations are modelled as fuzzy numbers. We take a fuzzy goal programming approach to propose a generic multiobjective model based on lexicographical minimisation of expected values. To solve the resulting problem, we propose a genetic algorithm searching in the space of possibly active schedules. Experimental results are presented for several problem instances, solved by the GA according to the proposed model, considering three objectives: makespan, tardiness and idleness. The results illustrate the potential of the proposed multiobjective model and genetic algorithm
dc.description.sponsorshipAll authors are supported by MEC-FEDER Grant TIN2007- 67466-C02-01
dc.format.extentp. 65-73spa
dc.language.isoeng
dc.publisherSpringer
dc.relation.ispartofJournal of Intelligent Manufacturing, 21(1)spa
dc.rights© Springer
dc.titleA genetic solution based on lexicographical goal programming for a multiobjective job shop with uncertaintyeng
dc.typejournal article
dc.identifier.local20100737spa
dc.identifier.doi10.1007/s10845-008-0161-x
dc.relation.projectIDMEC-FEDER/TIN2007-67466-C02-01
dc.relation.publisherversionhttp://dx.doi.org/10.1007/s10845-008-0161-xspa
dc.rights.accessRightsopen access
dc.type.hasVersionAM


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