Handling uncertainty in the quay crane scheduling problem: a unified distributionally robust decision model
Autor(a) principal: | |
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Data de Publicação: | 2024 |
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/10773/39950 |
Resumo: | Quay cranes are among the most important resources in port terminals, and their efficient use is crucial for port terminals to remain competitive in the market. The problem of determining the sequence of tasks performed by the quay cranes that minimizes the turnaround time of a vessel is an NP-hard problem known as the quay crane scheduling problem (QCSP). In this paper, we consider the unidirectional QCSP under uncertain processing times, where the cranes are only allowed to move in a specific direction. We start by presenting the first distributionally robust optimization (DRO) model for this problem and an exact decomposition algorithm to solve it. The proposed DRO model makes it possible to derive a stochastic programming model and a robust optimization model for the unidirectional QCSP by an appropriate choice of the risk-averse parameter of the model. Through extensive numerical results, we compare these three approaches—stochastic programming, robust optimization, and DRO—to investigate whether significant differences among the solutions obtained exist. Finally, we propose a new method for helping practitioners to determine a representative set of different DRO solutions. |
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7160 |
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Handling uncertainty in the quay crane scheduling problem: a unified distributionally robust decision modelQuay crane schedulingDistributionally robust optimizationWasserstein distanceUncertaintyUnidirectionalQuay cranes are among the most important resources in port terminals, and their efficient use is crucial for port terminals to remain competitive in the market. The problem of determining the sequence of tasks performed by the quay cranes that minimizes the turnaround time of a vessel is an NP-hard problem known as the quay crane scheduling problem (QCSP). In this paper, we consider the unidirectional QCSP under uncertain processing times, where the cranes are only allowed to move in a specific direction. We start by presenting the first distributionally robust optimization (DRO) model for this problem and an exact decomposition algorithm to solve it. The proposed DRO model makes it possible to derive a stochastic programming model and a robust optimization model for the unidirectional QCSP by an appropriate choice of the risk-averse parameter of the model. Through extensive numerical results, we compare these three approaches—stochastic programming, robust optimization, and DRO—to investigate whether significant differences among the solutions obtained exist. Finally, we propose a new method for helping practitioners to determine a representative set of different DRO solutions.Wiley2024-01-04T15:35:38Z2024-03-01T00:00:00Z2024-03info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10773/39950eng0969-601610.1111/itor.13325Rodrigues, FilipeAgra, Agostinhoinfo: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:RCAAP2024-02-22T12:17:57Zoai:ria.ua.pt:10773/39950Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:09:58.018382Repositório 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 |
Handling uncertainty in the quay crane scheduling problem: a unified distributionally robust decision model |
title |
Handling uncertainty in the quay crane scheduling problem: a unified distributionally robust decision model |
spellingShingle |
Handling uncertainty in the quay crane scheduling problem: a unified distributionally robust decision model Rodrigues, Filipe Quay crane scheduling Distributionally robust optimization Wasserstein distance Uncertainty Unidirectional |
title_short |
Handling uncertainty in the quay crane scheduling problem: a unified distributionally robust decision model |
title_full |
Handling uncertainty in the quay crane scheduling problem: a unified distributionally robust decision model |
title_fullStr |
Handling uncertainty in the quay crane scheduling problem: a unified distributionally robust decision model |
title_full_unstemmed |
Handling uncertainty in the quay crane scheduling problem: a unified distributionally robust decision model |
title_sort |
Handling uncertainty in the quay crane scheduling problem: a unified distributionally robust decision model |
author |
Rodrigues, Filipe |
author_facet |
Rodrigues, Filipe Agra, Agostinho |
author_role |
author |
author2 |
Agra, Agostinho |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Rodrigues, Filipe Agra, Agostinho |
dc.subject.por.fl_str_mv |
Quay crane scheduling Distributionally robust optimization Wasserstein distance Uncertainty Unidirectional |
topic |
Quay crane scheduling Distributionally robust optimization Wasserstein distance Uncertainty Unidirectional |
description |
Quay cranes are among the most important resources in port terminals, and their efficient use is crucial for port terminals to remain competitive in the market. The problem of determining the sequence of tasks performed by the quay cranes that minimizes the turnaround time of a vessel is an NP-hard problem known as the quay crane scheduling problem (QCSP). In this paper, we consider the unidirectional QCSP under uncertain processing times, where the cranes are only allowed to move in a specific direction. We start by presenting the first distributionally robust optimization (DRO) model for this problem and an exact decomposition algorithm to solve it. The proposed DRO model makes it possible to derive a stochastic programming model and a robust optimization model for the unidirectional QCSP by an appropriate choice of the risk-averse parameter of the model. Through extensive numerical results, we compare these three approaches—stochastic programming, robust optimization, and DRO—to investigate whether significant differences among the solutions obtained exist. Finally, we propose a new method for helping practitioners to determine a representative set of different DRO solutions. |
publishDate |
2024 |
dc.date.none.fl_str_mv |
2024-01-04T15:35:38Z 2024-03-01T00:00:00Z 2024-03 |
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/10773/39950 |
url |
http://hdl.handle.net/10773/39950 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
0969-6016 10.1111/itor.13325 |
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 |
Wiley |
publisher.none.fl_str_mv |
Wiley |
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 |
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1799137750247538688 |