Simulation-optimization models for the dynamic berth allocation problem

Container terminals are designed to provide support for the continuous changes in container ships. The most common schemes used for dock management are based on discrete and continuous locations. In view of the steadily growing trend in increasing container ship size, more flexible berth allocation...

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Detalhes bibliográficos
Autores: Arango Pastrana, Carlos Alberto, Cortés, Pablo, Onieva, Luis, Escudero Santana, Alejandro
Formato: artículo
Estado:Versión enviada para evaluación y publicación
Fecha de publicación:2013
País:España
Recursos:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/41345
Acesso em linha:http://hdl.handle.net/11441/41345
https://doi.org/10.1111/mice.12049
Access Level:acceso abierto
Palavra-chave:Berth allocation
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spelling Simulation-optimization models for the dynamic berth allocation problemArango Pastrana, Carlos AlbertoCortés, PabloOnieva, LuisEscudero Santana, AlejandroBerth allocationContainer terminals are designed to provide support for the continuous changes in container ships. The most common schemes used for dock management are based on discrete and continuous locations. In view of the steadily growing trend in increasing container ship size, more flexible berth allocation planning is mandatory. The consideration of continuous location in the container terminal is a good option. This paper addresses the berth allocation problem with continuous dock, which is called dynamic berth allocation problem (DBAP). We propose a mathematical model and develop a heuristic procedure, based on a genetic algorithm, to solve the corresponding mixed integer problem. Allocation planning aims to minimise distances travelled by the forklifts and the quay crane, for container loading and unloading operations for each ship, according to the quay crane scheduling. Simulations are undertaken using Arena software, and experimental analysis is carried out for the most important container terminal in Spain.Blackwell PublishingOrganización Industrial y Gestión de Empresas IITEP127: Ingeniería de Organización2013info:eu-repo/semantics/articleinfo:eu-repo/semantics/submittedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/11441/41345https://doi.org/10.1111/mice.12049reponame:idUS. Depósito de Investigación de la Universidad de Sevillainstname:Universidad de Sevilla (US)InglésComputer-aided Civil and Infrastructure Engineering, 28, 769-779.http://dx.doi.org/10.1111/mice.12049info:eu-repo/semantics/openAccessoai:idus.us.es:11441/413452026-06-17T12:51:07Z
dc.title.none.fl_str_mv Simulation-optimization models for the dynamic berth allocation problem
title Simulation-optimization models for the dynamic berth allocation problem
spellingShingle Simulation-optimization models for the dynamic berth allocation problem
Arango Pastrana, Carlos Alberto
Berth allocation
title_short Simulation-optimization models for the dynamic berth allocation problem
title_full Simulation-optimization models for the dynamic berth allocation problem
title_fullStr Simulation-optimization models for the dynamic berth allocation problem
title_full_unstemmed Simulation-optimization models for the dynamic berth allocation problem
title_sort Simulation-optimization models for the dynamic berth allocation problem
dc.creator.none.fl_str_mv Arango Pastrana, Carlos Alberto
Cortés, Pablo
Onieva, Luis
Escudero Santana, Alejandro
author Arango Pastrana, Carlos Alberto
author_facet Arango Pastrana, Carlos Alberto
Cortés, Pablo
Onieva, Luis
Escudero Santana, Alejandro
author_role author
author2 Cortés, Pablo
Onieva, Luis
Escudero Santana, Alejandro
author2_role author
author
author
dc.contributor.none.fl_str_mv Organización Industrial y Gestión de Empresas II
TEP127: Ingeniería de Organización
dc.subject.none.fl_str_mv Berth allocation
topic Berth allocation
description Container terminals are designed to provide support for the continuous changes in container ships. The most common schemes used for dock management are based on discrete and continuous locations. In view of the steadily growing trend in increasing container ship size, more flexible berth allocation planning is mandatory. The consideration of continuous location in the container terminal is a good option. This paper addresses the berth allocation problem with continuous dock, which is called dynamic berth allocation problem (DBAP). We propose a mathematical model and develop a heuristic procedure, based on a genetic algorithm, to solve the corresponding mixed integer problem. Allocation planning aims to minimise distances travelled by the forklifts and the quay crane, for container loading and unloading operations for each ship, according to the quay crane scheduling. Simulations are undertaken using Arena software, and experimental analysis is carried out for the most important container terminal in Spain.
publishDate 2013
dc.date.none.fl_str_mv 2013
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/submittedVersion
format article
status_str submittedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11441/41345
https://doi.org/10.1111/mice.12049
url http://hdl.handle.net/11441/41345
https://doi.org/10.1111/mice.12049
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Computer-aided Civil and Infrastructure Engineering, 28, 769-779.
http://dx.doi.org/10.1111/mice.12049
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Blackwell Publishing
publisher.none.fl_str_mv Blackwell Publishing
dc.source.none.fl_str_mv reponame:idUS. Depósito de Investigación de la Universidad de Sevilla
instname:Universidad de Sevilla (US)
instname_str Universidad de Sevilla (US)
reponame_str idUS. Depósito de Investigación de la Universidad de Sevilla
collection idUS. Depósito de Investigación de la Universidad de Sevilla
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,300719

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