A Hybrid Local Improvement Algorithm for Large-scale Multi-depot Vehicle Routing Problems with Time Windows

Autores
Dondo, Rodolfo Gabriel; Cerda, Jaime
Año de publicación
2009
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
One of the major research topics in the supply chain management field is the multi-depot vehicle routing problem with time windows (m-VRPTW). It aims to designing a set of minimum-cost routes for a vehicle fleet servicing many customers with known demands and predefined time windows. This paper presents an m-VRPTW local search improvement algorithm that explores a large neighborhood of the current solution to discover a cheaper set of feasible routes. The neighborhood structure comprises all solutions that can be generated by iteratively performing node exchanges among nearby trips followed by a node reordering on every route. Manageable mixed-integer linear programming (MILP) formulations for both algorithmic steps were developed. To further reduce the problem size, a spatial decomposition scheme has also been applied. A significant number of large-scale benchmark problems, some of them including up to 200 customers, multiple depots and different vehicle-types, were solved in quite reasonable CPU times.
Fil: Dondo, Rodolfo Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentina
Fil: Cerda, Jaime. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentina
Materia
Large-Scale Vehicle Routing Problems
Time Windows
Multi-Depot
Improvement Algorithm
Hybrid Approach
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/25443
Acceder
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network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling A Hybrid Local Improvement Algorithm for Large-scale Multi-depot Vehicle Routing Problems with Time WindowsDondo, Rodolfo GabrielCerda, JaimeLarge-Scale Vehicle Routing ProblemsTime WindowsMulti-DepotImprovement AlgorithmHybrid Approachhttps://purl.org/becyt/ford/2.4https://purl.org/becyt/ford/2One of the major research topics in the supply chain management field is the multi-depot vehicle routing problem with time windows (m-VRPTW). It aims to designing a set of minimum-cost routes for a vehicle fleet servicing many customers with known demands and predefined time windows. This paper presents an m-VRPTW local search improvement algorithm that explores a large neighborhood of the current solution to discover a cheaper set of feasible routes. The neighborhood structure comprises all solutions that can be generated by iteratively performing node exchanges among nearby trips followed by a node reordering on every route. Manageable mixed-integer linear programming (MILP) formulations for both algorithmic steps were developed. To further reduce the problem size, a spatial decomposition scheme has also been applied. A significant number of large-scale benchmark problems, some of them including up to 200 customers, multiple depots and different vehicle-types, were solved in quite reasonable CPU times.Fil: Dondo, Rodolfo Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: Cerda, Jaime. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaElsevier Ireland2009-02info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/25443Dondo, Rodolfo Gabriel; Cerda, Jaime; A Hybrid Local Improvement Algorithm for Large-scale Multi-depot Vehicle Routing Problems with Time Windows; Elsevier Ireland; Computers and Chemical Engineering; 33; 2; 2-2009; 513-5300098-1354CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.compchemeng.2008.10.003info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0098135408002081info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:02:35Zoai:ri.conicet.gov.ar:11336/25443instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:02:35.707CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A Hybrid Local Improvement Algorithm for Large-scale Multi-depot Vehicle Routing Problems with Time Windows
title A Hybrid Local Improvement Algorithm for Large-scale Multi-depot Vehicle Routing Problems with Time Windows
spellingShingle A Hybrid Local Improvement Algorithm for Large-scale Multi-depot Vehicle Routing Problems with Time Windows
Dondo, Rodolfo Gabriel
Large-Scale Vehicle Routing Problems
Time Windows
Multi-Depot
Improvement Algorithm
Hybrid Approach
title_short A Hybrid Local Improvement Algorithm for Large-scale Multi-depot Vehicle Routing Problems with Time Windows
title_full A Hybrid Local Improvement Algorithm for Large-scale Multi-depot Vehicle Routing Problems with Time Windows
title_fullStr A Hybrid Local Improvement Algorithm for Large-scale Multi-depot Vehicle Routing Problems with Time Windows
title_full_unstemmed A Hybrid Local Improvement Algorithm for Large-scale Multi-depot Vehicle Routing Problems with Time Windows
title_sort A Hybrid Local Improvement Algorithm for Large-scale Multi-depot Vehicle Routing Problems with Time Windows
dc.creator.none.fl_str_mv Dondo, Rodolfo Gabriel
Cerda, Jaime
author Dondo, Rodolfo Gabriel
author_facet Dondo, Rodolfo Gabriel
Cerda, Jaime
author_role author
author2 Cerda, Jaime
author2_role author
dc.subject.none.fl_str_mv Large-Scale Vehicle Routing Problems
Time Windows
Multi-Depot
Improvement Algorithm
Hybrid Approach
topic Large-Scale Vehicle Routing Problems
Time Windows
Multi-Depot
Improvement Algorithm
Hybrid Approach
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.4
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv One of the major research topics in the supply chain management field is the multi-depot vehicle routing problem with time windows (m-VRPTW). It aims to designing a set of minimum-cost routes for a vehicle fleet servicing many customers with known demands and predefined time windows. This paper presents an m-VRPTW local search improvement algorithm that explores a large neighborhood of the current solution to discover a cheaper set of feasible routes. The neighborhood structure comprises all solutions that can be generated by iteratively performing node exchanges among nearby trips followed by a node reordering on every route. Manageable mixed-integer linear programming (MILP) formulations for both algorithmic steps were developed. To further reduce the problem size, a spatial decomposition scheme has also been applied. A significant number of large-scale benchmark problems, some of them including up to 200 customers, multiple depots and different vehicle-types, were solved in quite reasonable CPU times.
Fil: Dondo, Rodolfo Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentina
Fil: Cerda, Jaime. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentina
description One of the major research topics in the supply chain management field is the multi-depot vehicle routing problem with time windows (m-VRPTW). It aims to designing a set of minimum-cost routes for a vehicle fleet servicing many customers with known demands and predefined time windows. This paper presents an m-VRPTW local search improvement algorithm that explores a large neighborhood of the current solution to discover a cheaper set of feasible routes. The neighborhood structure comprises all solutions that can be generated by iteratively performing node exchanges among nearby trips followed by a node reordering on every route. Manageable mixed-integer linear programming (MILP) formulations for both algorithmic steps were developed. To further reduce the problem size, a spatial decomposition scheme has also been applied. A significant number of large-scale benchmark problems, some of them including up to 200 customers, multiple depots and different vehicle-types, were solved in quite reasonable CPU times.
publishDate 2009
dc.date.none.fl_str_mv 2009-02
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/25443
Dondo, Rodolfo Gabriel; Cerda, Jaime; A Hybrid Local Improvement Algorithm for Large-scale Multi-depot Vehicle Routing Problems with Time Windows; Elsevier Ireland; Computers and Chemical Engineering; 33; 2; 2-2009; 513-530
0098-1354
CONICET Digital
CONICET
url http://hdl.handle.net/11336/25443
identifier_str_mv Dondo, Rodolfo Gabriel; Cerda, Jaime; A Hybrid Local Improvement Algorithm for Large-scale Multi-depot Vehicle Routing Problems with Time Windows; Elsevier Ireland; Computers and Chemical Engineering; 33; 2; 2-2009; 513-530
0098-1354
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.compchemeng.2008.10.003
info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0098135408002081
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier Ireland
publisher.none.fl_str_mv Elsevier Ireland
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.070432

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