INTEGER FORMULATIONS FOR THE INTEGRATED VEHICLE ROUTING PROBLEM WITH TWO-DIMENSIONAL PACKING CONSTRAINTS
Autor(a) principal: | |
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Data de Publicação: | 2022 |
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=S0101-74382022000100207 |
Resumo: | ABSTRACT Two integer linear programming models are developed for the unrestricted vehicle routing problem with two-dimensional loading constraints. The first one is a complete model, and the other uses valid inequalities to guarantee that routes are connected and respect the two-dimensional loading constraints. The models are solved with a branch-and-cut algorithm. Computational experiments on benchmark instances showed the complete model has allowed optimal solutions for 5% of the instances, while the second model optimally solved 64% of the instances. Given the superior performance of the second model, we adapted it to handle the sequential variant of the problem, which is harder, and then optimal solutions were obtained for 46% of the instances within the given time limit. The second model compared with a branch-and-cut algorithm from the literature found identical or better solutions for all the instances. |
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INTEGER FORMULATIONS FOR THE INTEGRATED VEHICLE ROUTING PROBLEM WITH TWO-DIMENSIONAL PACKING CONSTRAINTSvehicle routing problem with two-dimensional loadingmulti-drop requirementsinteger programming formulationbranch-and-cutABSTRACT Two integer linear programming models are developed for the unrestricted vehicle routing problem with two-dimensional loading constraints. The first one is a complete model, and the other uses valid inequalities to guarantee that routes are connected and respect the two-dimensional loading constraints. The models are solved with a branch-and-cut algorithm. Computational experiments on benchmark instances showed the complete model has allowed optimal solutions for 5% of the instances, while the second model optimally solved 64% of the instances. Given the superior performance of the second model, we adapted it to handle the sequential variant of the problem, which is harder, and then optimal solutions were obtained for 46% of the instances within the given time limit. The second model compared with a branch-and-cut algorithm from the literature found identical or better solutions for all the instances.Sociedade Brasileira de Pesquisa Operacional2022-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382022000100207Pesquisa Operacional v.42 2022reponame:Pesquisa operacional (Online)instname:Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)instacron:SOBRAPO10.1590/0101-7438.2022.042.00248686info:eu-repo/semantics/openAccessSilva,Lorrany Cristina daQueiroz,Thiago Alves deToledo,Franklina Maria Bragion deeng2022-04-27T00:00:00Zoai:scielo:S0101-74382022000100207Revistahttp://www.scielo.br/popehttps://old.scielo.br/oai/scielo-oai.php||sobrapo@sobrapo.org.br1678-51420101-7438opendoar:2022-04-27T00:00Pesquisa operacional (Online) - Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)false |
dc.title.none.fl_str_mv |
INTEGER FORMULATIONS FOR THE INTEGRATED VEHICLE ROUTING PROBLEM WITH TWO-DIMENSIONAL PACKING CONSTRAINTS |
title |
INTEGER FORMULATIONS FOR THE INTEGRATED VEHICLE ROUTING PROBLEM WITH TWO-DIMENSIONAL PACKING CONSTRAINTS |
spellingShingle |
INTEGER FORMULATIONS FOR THE INTEGRATED VEHICLE ROUTING PROBLEM WITH TWO-DIMENSIONAL PACKING CONSTRAINTS Silva,Lorrany Cristina da vehicle routing problem with two-dimensional loading multi-drop requirements integer programming formulation branch-and-cut |
title_short |
INTEGER FORMULATIONS FOR THE INTEGRATED VEHICLE ROUTING PROBLEM WITH TWO-DIMENSIONAL PACKING CONSTRAINTS |
title_full |
INTEGER FORMULATIONS FOR THE INTEGRATED VEHICLE ROUTING PROBLEM WITH TWO-DIMENSIONAL PACKING CONSTRAINTS |
title_fullStr |
INTEGER FORMULATIONS FOR THE INTEGRATED VEHICLE ROUTING PROBLEM WITH TWO-DIMENSIONAL PACKING CONSTRAINTS |
title_full_unstemmed |
INTEGER FORMULATIONS FOR THE INTEGRATED VEHICLE ROUTING PROBLEM WITH TWO-DIMENSIONAL PACKING CONSTRAINTS |
title_sort |
INTEGER FORMULATIONS FOR THE INTEGRATED VEHICLE ROUTING PROBLEM WITH TWO-DIMENSIONAL PACKING CONSTRAINTS |
author |
Silva,Lorrany Cristina da |
author_facet |
Silva,Lorrany Cristina da Queiroz,Thiago Alves de Toledo,Franklina Maria Bragion de |
author_role |
author |
author2 |
Queiroz,Thiago Alves de Toledo,Franklina Maria Bragion de |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Silva,Lorrany Cristina da Queiroz,Thiago Alves de Toledo,Franklina Maria Bragion de |
dc.subject.por.fl_str_mv |
vehicle routing problem with two-dimensional loading multi-drop requirements integer programming formulation branch-and-cut |
topic |
vehicle routing problem with two-dimensional loading multi-drop requirements integer programming formulation branch-and-cut |
description |
ABSTRACT Two integer linear programming models are developed for the unrestricted vehicle routing problem with two-dimensional loading constraints. The first one is a complete model, and the other uses valid inequalities to guarantee that routes are connected and respect the two-dimensional loading constraints. The models are solved with a branch-and-cut algorithm. Computational experiments on benchmark instances showed the complete model has allowed optimal solutions for 5% of the instances, while the second model optimally solved 64% of the instances. Given the superior performance of the second model, we adapted it to handle the sequential variant of the problem, which is harder, and then optimal solutions were obtained for 46% of the instances within the given time limit. The second model compared with a branch-and-cut algorithm from the literature found identical or better solutions for all the instances. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-01-01 |
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=S0101-74382022000100207 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382022000100207 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/0101-7438.2022.042.00248686 |
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.42 2022 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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1750318018499444736 |