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Tabu search and genetic algorithm for scheduling with total flow time minimization

dc.contributor.authorGonzález Fernández, Miguel Ángel 
dc.contributor.authorRodríguez Vela, María del Camino 
dc.contributor.authorSierra Sánchez, María Rita 
dc.contributor.authorVarela Arias, José Ramiro 
dc.date.accessioned2015-07-13T09:50:25Z
dc.date.available2015-07-13T09:50:25Z
dc.date.issued2010
dc.identifier.urihttp://hdl.handle.net/10651/31597
dc.description.abstractIn this paper we confront the job shop scheduling problem with total flow time minimization. We start extending the disjunctive graph model used for makespan minimization to represent the version of the problem with total flow time minimization. Using this representation, we adapt local search neighborhood structures originally defined for makespan minimization. The proposed neighborhood structures are used in a genetic algorithm hybridized with a simple tabu search method, outperforming state-of-the-art methods in solving problem instances from several datasetsspa
dc.format.extentp. 33-41spa
dc.language.isoengspa
dc.publisherAssociation for the Advancement of Artificial Intelligence (AAAI)spa
dc.relation.ispartofProceedings of the workshop on constraint satisfaction techniques for planning and scheduling problems (COPLAS)spa
dc.rights© 2010 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.titleTabu search and genetic algorithm for scheduling with total flow time minimizationspa
dc.typeconference outputspa
dc.rights.accessRightsopen accessspa


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