Solving Large Distribution Problems in Supply Chain Networks by a Column Generation Approach

Autores
Dondo, Rodolfo Gabriel; Mendez, Carlos Alberto
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Vehicle routing problems (VRP) are receiving a growing attention in process systems engineering due to its close relationship with supply chain issues. Its aim is to discover the best routes/schedules for a vehicles fleet fulfilling a number of transportation requests at minimum cost. Pick-up and delivery problems (PDP) are a class of VRP on which each request defines the shipping of a given load from a specified pickup site to a given customer. In order to account for a wider range of logistics problems, the so-called supply-chain management VRP (SCM-VRP) problem has been defined as a three-tier network of interconnected factories, warehouses and customers. In this problem, multiple products are to be delivered from some supply-sites to a number of customers through a routes-network in order to meet a set of given demands. The vehicle routes must satisfy capacity and timing constraints while minimizing an objective function stating the specified transportation cost. Pickup sites for each demand are decision variables rather than problem specifications. The SCM-VRP had been modeled as an MILP problem and the resolution of this formulation via a standard branch-and-cut software can provide optimal solutions to moderate size instances. In order to efficiently address larger problems, a decomposition method based on a column generation procedure is introduced in this work. In contrast to traditional columns generation approaches lying on dynamic-programming-procedures as route generators, an MILP formulation is here proposed to create the set of feasible routes and schedules at the slave level of the method. Furthermore, a branch-and-price method based on node-to-routes assignment decisions is constructed to better exploit the MILP route-generator. Finally, several benchmark examples were presented and satisfactorily solved.
Fil: Dondo, Rodolfo Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química (i); Argentina. Universidad Nacional del Litoral; Argentina
Fil: Mendez, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química (i); Argentina
Materia
Supply-Chain Management
Pick-Up And Delivery
Logistics
Columns Generation
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:11336/9266

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network_name_str CONICET Digital (CONICET)
spelling Solving Large Distribution Problems in Supply Chain Networks by a Column Generation ApproachDondo, Rodolfo GabrielMendez, Carlos AlbertoSupply-Chain ManagementPick-Up And DeliveryLogisticsColumns Generationhttps://purl.org/becyt/ford/2.11https://purl.org/becyt/ford/2Vehicle routing problems (VRP) are receiving a growing attention in process systems engineering due to its close relationship with supply chain issues. Its aim is to discover the best routes/schedules for a vehicles fleet fulfilling a number of transportation requests at minimum cost. Pick-up and delivery problems (PDP) are a class of VRP on which each request defines the shipping of a given load from a specified pickup site to a given customer. In order to account for a wider range of logistics problems, the so-called supply-chain management VRP (SCM-VRP) problem has been defined as a three-tier network of interconnected factories, warehouses and customers. In this problem, multiple products are to be delivered from some supply-sites to a number of customers through a routes-network in order to meet a set of given demands. The vehicle routes must satisfy capacity and timing constraints while minimizing an objective function stating the specified transportation cost. Pickup sites for each demand are decision variables rather than problem specifications. The SCM-VRP had been modeled as an MILP problem and the resolution of this formulation via a standard branch-and-cut software can provide optimal solutions to moderate size instances. In order to efficiently address larger problems, a decomposition method based on a column generation procedure is introduced in this work. In contrast to traditional columns generation approaches lying on dynamic-programming-procedures as route generators, an MILP formulation is here proposed to create the set of feasible routes and schedules at the slave level of the method. Furthermore, a branch-and-price method based on node-to-routes assignment decisions is constructed to better exploit the MILP route-generator. Finally, several benchmark examples were presented and satisfactorily solved.Fil: Dondo, Rodolfo Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química (i); Argentina. Universidad Nacional del Litoral; ArgentinaFil: Mendez, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química (i); ArgentinaIgi Global2014-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/9266Dondo, Rodolfo Gabriel; Mendez, Carlos Alberto; Solving Large Distribution Problems in Supply Chain Networks by a Column Generation Approach; Igi Global; International Journal of Operations Research and Information Systems; 5; 7-2014; 50-801947-9328enginfo:eu-repo/semantics/altIdentifier/url/http://www.igi-global.com/article/solving-large-distribution-problems-in-supply-chain-networks-by-a-column-generation-approach/117779info:eu-repo/semantics/altIdentifier/doi/10.4018/ijoris.2014070103info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T15:20:50Zoai:ri.conicet.gov.ar:11336/9266instacron: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:34982025-10-15 15:20:50.301CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Solving Large Distribution Problems in Supply Chain Networks by a Column Generation Approach
title Solving Large Distribution Problems in Supply Chain Networks by a Column Generation Approach
spellingShingle Solving Large Distribution Problems in Supply Chain Networks by a Column Generation Approach
Dondo, Rodolfo Gabriel
Supply-Chain Management
Pick-Up And Delivery
Logistics
Columns Generation
title_short Solving Large Distribution Problems in Supply Chain Networks by a Column Generation Approach
title_full Solving Large Distribution Problems in Supply Chain Networks by a Column Generation Approach
title_fullStr Solving Large Distribution Problems in Supply Chain Networks by a Column Generation Approach
title_full_unstemmed Solving Large Distribution Problems in Supply Chain Networks by a Column Generation Approach
title_sort Solving Large Distribution Problems in Supply Chain Networks by a Column Generation Approach
dc.creator.none.fl_str_mv Dondo, Rodolfo Gabriel
Mendez, Carlos Alberto
author Dondo, Rodolfo Gabriel
author_facet Dondo, Rodolfo Gabriel
Mendez, Carlos Alberto
author_role author
author2 Mendez, Carlos Alberto
author2_role author
dc.subject.none.fl_str_mv Supply-Chain Management
Pick-Up And Delivery
Logistics
Columns Generation
topic Supply-Chain Management
Pick-Up And Delivery
Logistics
Columns Generation
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.11
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv Vehicle routing problems (VRP) are receiving a growing attention in process systems engineering due to its close relationship with supply chain issues. Its aim is to discover the best routes/schedules for a vehicles fleet fulfilling a number of transportation requests at minimum cost. Pick-up and delivery problems (PDP) are a class of VRP on which each request defines the shipping of a given load from a specified pickup site to a given customer. In order to account for a wider range of logistics problems, the so-called supply-chain management VRP (SCM-VRP) problem has been defined as a three-tier network of interconnected factories, warehouses and customers. In this problem, multiple products are to be delivered from some supply-sites to a number of customers through a routes-network in order to meet a set of given demands. The vehicle routes must satisfy capacity and timing constraints while minimizing an objective function stating the specified transportation cost. Pickup sites for each demand are decision variables rather than problem specifications. The SCM-VRP had been modeled as an MILP problem and the resolution of this formulation via a standard branch-and-cut software can provide optimal solutions to moderate size instances. In order to efficiently address larger problems, a decomposition method based on a column generation procedure is introduced in this work. In contrast to traditional columns generation approaches lying on dynamic-programming-procedures as route generators, an MILP formulation is here proposed to create the set of feasible routes and schedules at the slave level of the method. Furthermore, a branch-and-price method based on node-to-routes assignment decisions is constructed to better exploit the MILP route-generator. Finally, several benchmark examples were presented and satisfactorily solved.
Fil: Dondo, Rodolfo Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química (i); Argentina. Universidad Nacional del Litoral; Argentina
Fil: Mendez, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química (i); Argentina
description Vehicle routing problems (VRP) are receiving a growing attention in process systems engineering due to its close relationship with supply chain issues. Its aim is to discover the best routes/schedules for a vehicles fleet fulfilling a number of transportation requests at minimum cost. Pick-up and delivery problems (PDP) are a class of VRP on which each request defines the shipping of a given load from a specified pickup site to a given customer. In order to account for a wider range of logistics problems, the so-called supply-chain management VRP (SCM-VRP) problem has been defined as a three-tier network of interconnected factories, warehouses and customers. In this problem, multiple products are to be delivered from some supply-sites to a number of customers through a routes-network in order to meet a set of given demands. The vehicle routes must satisfy capacity and timing constraints while minimizing an objective function stating the specified transportation cost. Pickup sites for each demand are decision variables rather than problem specifications. The SCM-VRP had been modeled as an MILP problem and the resolution of this formulation via a standard branch-and-cut software can provide optimal solutions to moderate size instances. In order to efficiently address larger problems, a decomposition method based on a column generation procedure is introduced in this work. In contrast to traditional columns generation approaches lying on dynamic-programming-procedures as route generators, an MILP formulation is here proposed to create the set of feasible routes and schedules at the slave level of the method. Furthermore, a branch-and-price method based on node-to-routes assignment decisions is constructed to better exploit the MILP route-generator. Finally, several benchmark examples were presented and satisfactorily solved.
publishDate 2014
dc.date.none.fl_str_mv 2014-07
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/11336/9266
Dondo, Rodolfo Gabriel; Mendez, Carlos Alberto; Solving Large Distribution Problems in Supply Chain Networks by a Column Generation Approach; Igi Global; International Journal of Operations Research and Information Systems; 5; 7-2014; 50-80
1947-9328
url http://hdl.handle.net/11336/9266
identifier_str_mv Dondo, Rodolfo Gabriel; Mendez, Carlos Alberto; Solving Large Distribution Problems in Supply Chain Networks by a Column Generation Approach; Igi Global; International Journal of Operations Research and Information Systems; 5; 7-2014; 50-80
1947-9328
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.igi-global.com/article/solving-large-distribution-problems-in-supply-chain-networks-by-a-column-generation-approach/117779
info:eu-repo/semantics/altIdentifier/doi/10.4018/ijoris.2014070103
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
dc.publisher.none.fl_str_mv Igi Global
publisher.none.fl_str_mv Igi Global
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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