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A new hybrid genetic algorithm for the job shop scheduling problem with setup times

dc.contributor.authorGonzález Fernández, Miguel Ángel 
dc.contributor.authorRodríguez Vela, María del Camino 
dc.contributor.authorVarela Arias, José Ramiro 
dc.date.accessioned2015-07-10T09:55:51Z
dc.date.available2015-07-10T09:55:51Z
dc.date.issued2008
dc.identifier.urihttp://www.aaai.org/Papers/ICAPS/2008/ICAPS08-015.pdfspa
dc.identifier.urihttp://hdl.handle.net/10651/31584
dc.description.abstractIn this paper we face the Job Shop Scheduling Problem with Sequence Dependent Setup Times by means of a genetic algorithm hybridized with local search. We have built on a previous work and propose a new neighborhood structure for this problem which is based on reversing operations on a critical path. We have conducted an experimental study across the conventional benchmarks and some new ones of larger size. The results of these experiments show clearly that our approach outperforms the current state-of-the-art methodsspa
dc.format.extentp. 116-123spa
dc.language.isoengspa
dc.publisherAssociation for the Advancement of Artificial Intelligence (AAAI)spa
dc.relation.ispartofProceedings of the Eighteenth International Conference on Automated Planning and Scheduling (ICAPS 2008)spa
dc.rights© 2008, Association for the Advancement of Artificial Intelligence
dc.rightsCC Reconocimiento - No comercial - Sin obras derivadas 4.0 Internacional
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.titleA new hybrid genetic algorithm for the job shop scheduling problem with setup timeseng
dc.typeinfo:eu-repo/semantics/conferenceObjectspa
dc.type.dcmitextspa
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessspa


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© 2008, Association for the Advancement of Artificial
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