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A study of schedule robustness for job shop with uncertainty

dc.contributor.authorGonzález Rodríguez, Inés 
dc.contributor.authorPuente Peinador, Jorge 
dc.contributor.authorVarela Arias, José Ramiro 
dc.contributor.authorRodríguez Vela, María del Camino 
dc.date.accessioned2015-07-15T07:49:19Z
dc.date.available2015-07-15T07:49:19Z
dc.date.issued2008
dc.identifier.isbn978-3-540-88308-1
dc.identifier.urihttp://hdl.handle.net/10651/31969
dc.description11th Ibero-American Conference on AI, Lisbon, Portugalspa
dc.descriptionLa publicación final está disponible en Springer vía http://dx.doi.org/10.1007/978-3-540-88309-8_4
dc.description.abstractWe consider a job shop problem with uncertain processing times modelled as triangular fuzzy numbers and propose a methodology to study solution robustness with respect to different perturbations in the durations. This methodology is applied to obtain experimental results for several problem instances, using a hybrid genetic algorithm that minimises the expected makespan. We conclude that taking into account the uncertainty information provided by fuzzy numbers produces proactive solutions, coping well with posterior changes in processing times
dc.description.sponsorshipAll authors are supported by MEC-FEDER Grant TIN2007-67466-C02-01
dc.format.extentp. 31-41spa
dc.language.isoengspa
dc.publisherSpringerspa
dc.relation.ispartofAdvances in Artificial Intelligence–IBERAMIA 2008spa
dc.rights© 2008 Springer
dc.titleA study of schedule robustness for job shop with uncertaintyeng
dc.typeinfo:eu-repo/semantics/bookPartspa
dc.identifier.doi10.1007/978-3-540-88309-8_4
dc.type.dcmitextspa
dc.relation.projectIDMEC-FEDER/TIN2007-67466-C02-01
dc.relation.publisherversionhttp://dx.doi.org/10.1007/978-3-540-88309-8_4spa


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