METAHEURISTIC ANALYSIS APPLIED TO THE BERTH ALLOCATION PROBLEM: CASE STUDY IN A PORT CONTAINER TERMINAL

Detalhes bibliográficos
Autor(a) principal: Pereira,Elizangela Dias
Data de Publicação: 2018
Outros Autores: Coelho,Antonio Sérgio, Longaray,André Andrade, Machado,Catia Maria dos Santos, Munhoz,Paulo Roberto
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Pesquisa operacional (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382018000200247
Resumo: ABSTRACT The simulated annealing (SA) and genetic algorithm (GA) metaheuristics are comparatively applied to the berth allocation problem (BAP) of a port container terminal. By synthesizing the experimental studies of the BAP available in the literature, the two methods are compared when applied to the same case. For this purpose, six test problems are considered, where SA and GA are compared using four crossover operators. Once the optimal GA crossover operator is determined, computational tests are performed with the data obtained at the port terminal to compare the performance of the two metaheuristics.
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spelling METAHEURISTIC ANALYSIS APPLIED TO THE BERTH ALLOCATION PROBLEM: CASE STUDY IN A PORT CONTAINER TERMINALberth allocation problemgenetic algorithmsimulated annealingABSTRACT The simulated annealing (SA) and genetic algorithm (GA) metaheuristics are comparatively applied to the berth allocation problem (BAP) of a port container terminal. By synthesizing the experimental studies of the BAP available in the literature, the two methods are compared when applied to the same case. For this purpose, six test problems are considered, where SA and GA are compared using four crossover operators. Once the optimal GA crossover operator is determined, computational tests are performed with the data obtained at the port terminal to compare the performance of the two metaheuristics.Sociedade Brasileira de Pesquisa Operacional2018-08-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382018000200247Pesquisa Operacional v.38 n.2 2018reponame:Pesquisa operacional (Online)instname:Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)instacron:SOBRAPO10.1590/0101-7438.2018.038.02.0247info:eu-repo/semantics/openAccessPereira,Elizangela DiasCoelho,Antonio SérgioLongaray,André AndradeMachado,Catia Maria dos SantosMunhoz,Paulo Robertoeng2018-08-10T00:00:00Zoai:scielo:S0101-74382018000200247Revistahttp://www.scielo.br/popehttps://old.scielo.br/oai/scielo-oai.php||sobrapo@sobrapo.org.br1678-51420101-7438opendoar:2018-08-10T00:00Pesquisa operacional (Online) - Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)false
dc.title.none.fl_str_mv METAHEURISTIC ANALYSIS APPLIED TO THE BERTH ALLOCATION PROBLEM: CASE STUDY IN A PORT CONTAINER TERMINAL
title METAHEURISTIC ANALYSIS APPLIED TO THE BERTH ALLOCATION PROBLEM: CASE STUDY IN A PORT CONTAINER TERMINAL
spellingShingle METAHEURISTIC ANALYSIS APPLIED TO THE BERTH ALLOCATION PROBLEM: CASE STUDY IN A PORT CONTAINER TERMINAL
Pereira,Elizangela Dias
berth allocation problem
genetic algorithm
simulated annealing
title_short METAHEURISTIC ANALYSIS APPLIED TO THE BERTH ALLOCATION PROBLEM: CASE STUDY IN A PORT CONTAINER TERMINAL
title_full METAHEURISTIC ANALYSIS APPLIED TO THE BERTH ALLOCATION PROBLEM: CASE STUDY IN A PORT CONTAINER TERMINAL
title_fullStr METAHEURISTIC ANALYSIS APPLIED TO THE BERTH ALLOCATION PROBLEM: CASE STUDY IN A PORT CONTAINER TERMINAL
title_full_unstemmed METAHEURISTIC ANALYSIS APPLIED TO THE BERTH ALLOCATION PROBLEM: CASE STUDY IN A PORT CONTAINER TERMINAL
title_sort METAHEURISTIC ANALYSIS APPLIED TO THE BERTH ALLOCATION PROBLEM: CASE STUDY IN A PORT CONTAINER TERMINAL
author Pereira,Elizangela Dias
author_facet Pereira,Elizangela Dias
Coelho,Antonio Sérgio
Longaray,André Andrade
Machado,Catia Maria dos Santos
Munhoz,Paulo Roberto
author_role author
author2 Coelho,Antonio Sérgio
Longaray,André Andrade
Machado,Catia Maria dos Santos
Munhoz,Paulo Roberto
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Pereira,Elizangela Dias
Coelho,Antonio Sérgio
Longaray,André Andrade
Machado,Catia Maria dos Santos
Munhoz,Paulo Roberto
dc.subject.por.fl_str_mv berth allocation problem
genetic algorithm
simulated annealing
topic berth allocation problem
genetic algorithm
simulated annealing
description ABSTRACT The simulated annealing (SA) and genetic algorithm (GA) metaheuristics are comparatively applied to the berth allocation problem (BAP) of a port container terminal. By synthesizing the experimental studies of the BAP available in the literature, the two methods are compared when applied to the same case. For this purpose, six test problems are considered, where SA and GA are compared using four crossover operators. Once the optimal GA crossover operator is determined, computational tests are performed with the data obtained at the port terminal to compare the performance of the two metaheuristics.
publishDate 2018
dc.date.none.fl_str_mv 2018-08-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382018000200247
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382018000200247
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0101-7438.2018.038.02.0247
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Sociedade Brasileira de Pesquisa Operacional
publisher.none.fl_str_mv Sociedade Brasileira de Pesquisa Operacional
dc.source.none.fl_str_mv Pesquisa Operacional v.38 n.2 2018
reponame:Pesquisa operacional (Online)
instname:Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)
instacron:SOBRAPO
instname_str Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)
instacron_str SOBRAPO
institution SOBRAPO
reponame_str Pesquisa operacional (Online)
collection Pesquisa operacional (Online)
repository.name.fl_str_mv Pesquisa operacional (Online) - Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)
repository.mail.fl_str_mv ||sobrapo@sobrapo.org.br
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