Distributionally robust optimization for the berth allocation problem under uncertainty
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10773/35199 |
Resumo: | Berth allocation problems are amongst the most important problems occurring in port terminals, and they are greatly affected by several unpredictable events. As a result, the study of these problems under uncertainty has been a target of more and more researchers. Following this research line, we consider the berth allocation problem under uncertain handling times. A distributionally robust two-stage model is presented to minimize the worst-case of the expected sum of delays with respect to a set of possible probability distributions of the handling times. The solutions of the proposed model are obtained by an exact decomposition algorithm for which several improvements are discussed. An adaptation of the proposed algorithm for the case where the assumption of relatively complete recourse fails is also presented. Extensive computational tests are reported to evaluate the effectiveness of the proposed approach and to compare the solutions obtained with those resulting from the stochastic and robust approaches. |
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Distributionally robust optimization for the berth allocation problem under uncertaintyBerth allocationDistributionally robust optimizationUncertain handling timesDecomposition algorithmWasserstein distanceBerth allocation problems are amongst the most important problems occurring in port terminals, and they are greatly affected by several unpredictable events. As a result, the study of these problems under uncertainty has been a target of more and more researchers. Following this research line, we consider the berth allocation problem under uncertain handling times. A distributionally robust two-stage model is presented to minimize the worst-case of the expected sum of delays with respect to a set of possible probability distributions of the handling times. The solutions of the proposed model are obtained by an exact decomposition algorithm for which several improvements are discussed. An adaptation of the proposed algorithm for the case where the assumption of relatively complete recourse fails is also presented. Extensive computational tests are reported to evaluate the effectiveness of the proposed approach and to compare the solutions obtained with those resulting from the stochastic and robust approaches.Elsevier2022-11-17T16:20:26Z2022-10-01T00:00:00Z2022-10info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10773/35199eng0191-261510.1016/j.trb.2022.07.009Agra, AgostinhoRodrigues, Filipeinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-02-22T12:07:38Zoai:ria.ua.pt:10773/35199Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:06:13.424283Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Distributionally robust optimization for the berth allocation problem under uncertainty |
title |
Distributionally robust optimization for the berth allocation problem under uncertainty |
spellingShingle |
Distributionally robust optimization for the berth allocation problem under uncertainty Agra, Agostinho Berth allocation Distributionally robust optimization Uncertain handling times Decomposition algorithm Wasserstein distance |
title_short |
Distributionally robust optimization for the berth allocation problem under uncertainty |
title_full |
Distributionally robust optimization for the berth allocation problem under uncertainty |
title_fullStr |
Distributionally robust optimization for the berth allocation problem under uncertainty |
title_full_unstemmed |
Distributionally robust optimization for the berth allocation problem under uncertainty |
title_sort |
Distributionally robust optimization for the berth allocation problem under uncertainty |
author |
Agra, Agostinho |
author_facet |
Agra, Agostinho Rodrigues, Filipe |
author_role |
author |
author2 |
Rodrigues, Filipe |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Agra, Agostinho Rodrigues, Filipe |
dc.subject.por.fl_str_mv |
Berth allocation Distributionally robust optimization Uncertain handling times Decomposition algorithm Wasserstein distance |
topic |
Berth allocation Distributionally robust optimization Uncertain handling times Decomposition algorithm Wasserstein distance |
description |
Berth allocation problems are amongst the most important problems occurring in port terminals, and they are greatly affected by several unpredictable events. As a result, the study of these problems under uncertainty has been a target of more and more researchers. Following this research line, we consider the berth allocation problem under uncertain handling times. A distributionally robust two-stage model is presented to minimize the worst-case of the expected sum of delays with respect to a set of possible probability distributions of the handling times. The solutions of the proposed model are obtained by an exact decomposition algorithm for which several improvements are discussed. An adaptation of the proposed algorithm for the case where the assumption of relatively complete recourse fails is also presented. Extensive computational tests are reported to evaluate the effectiveness of the proposed approach and to compare the solutions obtained with those resulting from the stochastic and robust approaches. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-11-17T16:20:26Z 2022-10-01T00:00:00Z 2022-10 |
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 |
http://hdl.handle.net/10773/35199 |
url |
http://hdl.handle.net/10773/35199 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
0191-2615 10.1016/j.trb.2022.07.009 |
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 |
Elsevier |
publisher.none.fl_str_mv |
Elsevier |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799137717300232192 |