A MATHEMATICAL MODEL AND GENECTIC ALGORITHM SOLUTION METHODS FOR THE BERTH ALLOCATION PROBLEM WITH SEVERAL TYPES OF MACHINES
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Pesquisa operacional (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382021000100201 |
Resumo: | ABSTRACT Maritime shipping is vital to worldwide commerce. Due to the high flow in ports throughout the world, the efficient allocation of vessels in berths has become a problem. A new mathematical model and several algorithms are proposed in this paper to planning the allocation of the vessels in berths and the allocation of resources to the service of each vessel. Those resources, in general, are machines to load or unload vessels. The mathematical model was implemented on Cplex and can solve small scale instances, due to its high complexity. To solve larger instances, a genetic algorithm-based metaheuristic, a first-in first-out heuristic, and a machine allocation algorithm are also proposed in this paper. The model and the algorithms produce very useful and interesting results. Comparing, the results produced by the GA are, on average, 94% better than the results of the Cplex and 26% better than the results of FIFO. |
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A MATHEMATICAL MODEL AND GENECTIC ALGORITHM SOLUTION METHODS FOR THE BERTH ALLOCATION PROBLEM WITH SEVERAL TYPES OF MACHINESBerth allocation problemallocation of port machinesoptimization of port processesABSTRACT Maritime shipping is vital to worldwide commerce. Due to the high flow in ports throughout the world, the efficient allocation of vessels in berths has become a problem. A new mathematical model and several algorithms are proposed in this paper to planning the allocation of the vessels in berths and the allocation of resources to the service of each vessel. Those resources, in general, are machines to load or unload vessels. The mathematical model was implemented on Cplex and can solve small scale instances, due to its high complexity. To solve larger instances, a genetic algorithm-based metaheuristic, a first-in first-out heuristic, and a machine allocation algorithm are also proposed in this paper. The model and the algorithms produce very useful and interesting results. Comparing, the results produced by the GA are, on average, 94% better than the results of the Cplex and 26% better than the results of FIFO.Sociedade Brasileira de Pesquisa Operacional2021-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382021000100201Pesquisa Operacional v.41 2021reponame:Pesquisa operacional (Online)instname:Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)instacron:SOBRAPO10.1590/0101-7438.2021.041.00239994info:eu-repo/semantics/openAccessCereser,Bruno Luís HönigmannSalles Neto,Luiz Leduíno deMoretti,Antonio CarlosOliveira,Aurelio Ribeiro Leite deeng2021-05-21T00:00:00Zoai:scielo:S0101-74382021000100201Revistahttp://www.scielo.br/popehttps://old.scielo.br/oai/scielo-oai.php||sobrapo@sobrapo.org.br1678-51420101-7438opendoar:2021-05-21T00:00Pesquisa operacional (Online) - Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)false |
dc.title.none.fl_str_mv |
A MATHEMATICAL MODEL AND GENECTIC ALGORITHM SOLUTION METHODS FOR THE BERTH ALLOCATION PROBLEM WITH SEVERAL TYPES OF MACHINES |
title |
A MATHEMATICAL MODEL AND GENECTIC ALGORITHM SOLUTION METHODS FOR THE BERTH ALLOCATION PROBLEM WITH SEVERAL TYPES OF MACHINES |
spellingShingle |
A MATHEMATICAL MODEL AND GENECTIC ALGORITHM SOLUTION METHODS FOR THE BERTH ALLOCATION PROBLEM WITH SEVERAL TYPES OF MACHINES Cereser,Bruno Luís Hönigmann Berth allocation problem allocation of port machines optimization of port processes |
title_short |
A MATHEMATICAL MODEL AND GENECTIC ALGORITHM SOLUTION METHODS FOR THE BERTH ALLOCATION PROBLEM WITH SEVERAL TYPES OF MACHINES |
title_full |
A MATHEMATICAL MODEL AND GENECTIC ALGORITHM SOLUTION METHODS FOR THE BERTH ALLOCATION PROBLEM WITH SEVERAL TYPES OF MACHINES |
title_fullStr |
A MATHEMATICAL MODEL AND GENECTIC ALGORITHM SOLUTION METHODS FOR THE BERTH ALLOCATION PROBLEM WITH SEVERAL TYPES OF MACHINES |
title_full_unstemmed |
A MATHEMATICAL MODEL AND GENECTIC ALGORITHM SOLUTION METHODS FOR THE BERTH ALLOCATION PROBLEM WITH SEVERAL TYPES OF MACHINES |
title_sort |
A MATHEMATICAL MODEL AND GENECTIC ALGORITHM SOLUTION METHODS FOR THE BERTH ALLOCATION PROBLEM WITH SEVERAL TYPES OF MACHINES |
author |
Cereser,Bruno Luís Hönigmann |
author_facet |
Cereser,Bruno Luís Hönigmann Salles Neto,Luiz Leduíno de Moretti,Antonio Carlos Oliveira,Aurelio Ribeiro Leite de |
author_role |
author |
author2 |
Salles Neto,Luiz Leduíno de Moretti,Antonio Carlos Oliveira,Aurelio Ribeiro Leite de |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Cereser,Bruno Luís Hönigmann Salles Neto,Luiz Leduíno de Moretti,Antonio Carlos Oliveira,Aurelio Ribeiro Leite de |
dc.subject.por.fl_str_mv |
Berth allocation problem allocation of port machines optimization of port processes |
topic |
Berth allocation problem allocation of port machines optimization of port processes |
description |
ABSTRACT Maritime shipping is vital to worldwide commerce. Due to the high flow in ports throughout the world, the efficient allocation of vessels in berths has become a problem. A new mathematical model and several algorithms are proposed in this paper to planning the allocation of the vessels in berths and the allocation of resources to the service of each vessel. Those resources, in general, are machines to load or unload vessels. The mathematical model was implemented on Cplex and can solve small scale instances, due to its high complexity. To solve larger instances, a genetic algorithm-based metaheuristic, a first-in first-out heuristic, and a machine allocation algorithm are also proposed in this paper. The model and the algorithms produce very useful and interesting results. Comparing, the results produced by the GA are, on average, 94% better than the results of the Cplex and 26% better than the results of FIFO. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-01-01 |
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=S0101-74382021000100201 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382021000100201 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/0101-7438.2021.041.00239994 |
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.41 2021 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 |
_version_ |
1750318018460647424 |