Please use this identifier to cite or link to this item: http://www.repositorio.ufc.br/handle/riufc/21182
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dc.contributor.authorPrata, Bruno de Athayde-
dc.date.accessioned2016-11-29T13:05:04Z-
dc.date.available2016-11-29T13:05:04Z-
dc.date.issued2016-04-
dc.identifier.citationPRATA, B. A. (2016)pt_BR
dc.identifier.issn2238-1031-
dc.identifier.urihttp://www.repositorio.ufc.br/handle/riufc/21182-
dc.descriptionPRATA, B. A. A Multiobjective metaheuristic approach for the integrated vehicle and crew scheduling. Journal of Transport Literature, [S.l.], v 10, n 2, p 10-14, abr. 2016.pt_BR
dc.description.abstractThe integrated vehicle and crew scheduling problem is a hard Combinatorial Optimization problem widely studied over the years. Taking into consideration the range of variables related to the planning process of vehicles and drivers, there are several practical characteristics of the problem that are not reflected in the solutions generated computationally. Among these characteristics, that were not found in the consulted literature, the most important is the existence of multiple objectives. This paper aims at presenting a multiobjective approach for the integrated vehicle and crew scheduling problem based on Genetic Algorithms. A case study in Portimão (Portugal) is presented and discussed. Were applied: (i) a Pareto Envelope-based Selection Algorithm II (PESA-II), and (ii) a hybridization between PESA-II and Integer Programming, which were summarized in a table. These results indicate that this new approach has a considerable potential for achieving significant gains in terms of operation costs and reduction in planning times.pt_BR
dc.language.isoenpt_BR
dc.publisherJournal of Transport Literaturept_BR
dc.subjectMass transitpt_BR
dc.subjectCombinatorial optimizationpt_BR
dc.subjectEvolutionary algorithmspt_BR
dc.subjectOtimização combinatóriapt_BR
dc.subjectAlgoritmospt_BR
dc.titleA Multiobjective metaheuristic approach for the integrated vehicle and crew schedulingpt_BR
dc.typeArtigo de Periódicopt_BR
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