A Multiobjective metaheuristic approach for the integrated vehicle and crew scheduling
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da Universidade Federal do Ceará (UFC) |
Texto Completo: | http://www.repositorio.ufc.br/handle/riufc/21182 |
Resumo: | The 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. |
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Repositório Institucional da Universidade Federal do Ceará (UFC) |
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A Multiobjective metaheuristic approach for the integrated vehicle and crew schedulingMass transitCombinatorial optimizationEvolutionary algorithmsOtimização combinatóriaAlgoritmosThe 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.Journal of Transport Literature2016-11-29T13:05:04Z2016-11-29T13:05:04Z2016info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfPRATA, 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. 2016.2238-1031http://www.repositorio.ufc.br/handle/riufc/21182Prata, Bruno de Athaydeengreponame:Repositório Institucional da Universidade Federal do Ceará (UFC)instname:Universidade Federal do Ceará (UFC)instacron:UFCinfo:eu-repo/semantics/openAccess2022-09-21T17:11:03Zoai:repositorio.ufc.br:riufc/21182Repositório InstitucionalPUBhttp://www.repositorio.ufc.br/ri-oai/requestbu@ufc.br || repositorio@ufc.bropendoar:2024-09-11T19:00:41.188067Repositório Institucional da Universidade Federal do Ceará (UFC) - Universidade Federal do Ceará (UFC)false |
dc.title.none.fl_str_mv |
A Multiobjective metaheuristic approach for the integrated vehicle and crew scheduling |
title |
A Multiobjective metaheuristic approach for the integrated vehicle and crew scheduling |
spellingShingle |
A Multiobjective metaheuristic approach for the integrated vehicle and crew scheduling Prata, Bruno de Athayde Mass transit Combinatorial optimization Evolutionary algorithms Otimização combinatória Algoritmos |
title_short |
A Multiobjective metaheuristic approach for the integrated vehicle and crew scheduling |
title_full |
A Multiobjective metaheuristic approach for the integrated vehicle and crew scheduling |
title_fullStr |
A Multiobjective metaheuristic approach for the integrated vehicle and crew scheduling |
title_full_unstemmed |
A Multiobjective metaheuristic approach for the integrated vehicle and crew scheduling |
title_sort |
A Multiobjective metaheuristic approach for the integrated vehicle and crew scheduling |
author |
Prata, Bruno de Athayde |
author_facet |
Prata, Bruno de Athayde |
author_role |
author |
dc.contributor.author.fl_str_mv |
Prata, Bruno de Athayde |
dc.subject.por.fl_str_mv |
Mass transit Combinatorial optimization Evolutionary algorithms Otimização combinatória Algoritmos |
topic |
Mass transit Combinatorial optimization Evolutionary algorithms Otimização combinatória Algoritmos |
description |
The 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. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-11-29T13:05:04Z 2016-11-29T13:05:04Z 2016 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
PRATA, 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. 2238-1031 http://www.repositorio.ufc.br/handle/riufc/21182 |
identifier_str_mv |
PRATA, 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. 2238-1031 |
url |
http://www.repositorio.ufc.br/handle/riufc/21182 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Journal of Transport Literature |
publisher.none.fl_str_mv |
Journal of Transport Literature |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da Universidade Federal do Ceará (UFC) instname:Universidade Federal do Ceará (UFC) instacron:UFC |
instname_str |
Universidade Federal do Ceará (UFC) |
instacron_str |
UFC |
institution |
UFC |
reponame_str |
Repositório Institucional da Universidade Federal do Ceará (UFC) |
collection |
Repositório Institucional da Universidade Federal do Ceará (UFC) |
repository.name.fl_str_mv |
Repositório Institucional da Universidade Federal do Ceará (UFC) - Universidade Federal do Ceará (UFC) |
repository.mail.fl_str_mv |
bu@ufc.br || repositorio@ufc.br |
_version_ |
1813029032651915264 |