Mixed integer linear programming approaches for solving the raw material allocation, routing and scheduling problems in the forest industry

Autores
Bordon, Maximiliano Ramon; Montagna, Jorge Marcelo; Corsano, Gabriela
Año de publicación
2020
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Transportation planning in forest industry is a challenging activity since it involves complex decisions about raw material allocation, vehicle routing and scheduling of trucks arrivals to both harvest areas and the plants. In the Argentine context, specifically in the Argentinean Northeast (NEA) region, the forest industry plays essential role for the economic development and, among the included activities, the transportation is the key element considering the volumes that must be moved and the distances to be traveled. Therefore, enhancing efficiency in the transportation activity improves significantly the performance of this industry. In this work, a Mixed Integer Linear Programming (MILP) model is presented, where raw material allocation, vehicle routing and scheduling of trucks arrivals are simultaneously addressed. Since the resolution times of the proposed integrated MILP model are prohibitive for large instances, a hierarchical approach is also presented. The considered decomposition approach involves two stages: in the first phase, the raw material allocation and vehicle routing problems are solved through a MILP model, while in the second phase, fixing the route for each truck according to the results of the previous step, the scheduling of truck arrivals to both the harvest areas and the plants is solved through a new MILP model. The obtained results show that the proposed approach is very effective and could be easily applied in this industry.
Fil: Bordon, Maximiliano Ramon. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
Fil: Montagna, Jorge Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
Fil: Corsano, Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
Materia
FOREST INDUSTRY
LOG TRANSPORTATION
MILP
SCHEDULING
VEHICLE ROUTING
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/136171
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/136171
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Mixed integer linear programming approaches for solving the raw material allocation, routing and scheduling problems in the forest industryBordon, Maximiliano RamonMontagna, Jorge MarceloCorsano, GabrielaFOREST INDUSTRYLOG TRANSPORTATIONMILPSCHEDULINGVEHICLE ROUTINGhttps://purl.org/becyt/ford/2.4https://purl.org/becyt/ford/2Transportation planning in forest industry is a challenging activity since it involves complex decisions about raw material allocation, vehicle routing and scheduling of trucks arrivals to both harvest areas and the plants. In the Argentine context, specifically in the Argentinean Northeast (NEA) region, the forest industry plays essential role for the economic development and, among the included activities, the transportation is the key element considering the volumes that must be moved and the distances to be traveled. Therefore, enhancing efficiency in the transportation activity improves significantly the performance of this industry. In this work, a Mixed Integer Linear Programming (MILP) model is presented, where raw material allocation, vehicle routing and scheduling of trucks arrivals are simultaneously addressed. Since the resolution times of the proposed integrated MILP model are prohibitive for large instances, a hierarchical approach is also presented. The considered decomposition approach involves two stages: in the first phase, the raw material allocation and vehicle routing problems are solved through a MILP model, while in the second phase, fixing the route for each truck according to the results of the previous step, the scheduling of truck arrivals to both the harvest areas and the plants is solved through a new MILP model. The obtained results show that the proposed approach is very effective and could be easily applied in this industry.Fil: Bordon, Maximiliano Ramon. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; ArgentinaFil: Montagna, Jorge Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; ArgentinaFil: Corsano, Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; ArgentinaGrowing Science2020-09info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/136171Bordon, Maximiliano Ramon; Montagna, Jorge Marcelo; Corsano, Gabriela; Mixed integer linear programming approaches for solving the raw material allocation, routing and scheduling problems in the forest industry; Growing Science; International Journal of Industrial Engineering Computations; 11; 4; 9-2020; 525-5481923-29261923-2934CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://growingscience.com/beta/ijiec/4020-mixed-integer-linear-programming-approaches-for-solving-the-raw-material-allocation-routing-and-scheduling-problems-in-the-forest-industry.htmlinfo:eu-repo/semantics/altIdentifier/doi/10.5267/j.ijiec.2020.5.001info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:43:46Zoai:ri.conicet.gov.ar:11336/136171instacron: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 09:43:46.343CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Mixed integer linear programming approaches for solving the raw material allocation, routing and scheduling problems in the forest industry
title Mixed integer linear programming approaches for solving the raw material allocation, routing and scheduling problems in the forest industry
spellingShingle Mixed integer linear programming approaches for solving the raw material allocation, routing and scheduling problems in the forest industry
Bordon, Maximiliano Ramon
FOREST INDUSTRY
LOG TRANSPORTATION
MILP
SCHEDULING
VEHICLE ROUTING
title_short Mixed integer linear programming approaches for solving the raw material allocation, routing and scheduling problems in the forest industry
title_full Mixed integer linear programming approaches for solving the raw material allocation, routing and scheduling problems in the forest industry
title_fullStr Mixed integer linear programming approaches for solving the raw material allocation, routing and scheduling problems in the forest industry
title_full_unstemmed Mixed integer linear programming approaches for solving the raw material allocation, routing and scheduling problems in the forest industry
title_sort Mixed integer linear programming approaches for solving the raw material allocation, routing and scheduling problems in the forest industry
dc.creator.none.fl_str_mv Bordon, Maximiliano Ramon
Montagna, Jorge Marcelo
Corsano, Gabriela
author Bordon, Maximiliano Ramon
author_facet Bordon, Maximiliano Ramon
Montagna, Jorge Marcelo
Corsano, Gabriela
author_role author
author2 Montagna, Jorge Marcelo
Corsano, Gabriela
author2_role author
author
dc.subject.none.fl_str_mv FOREST INDUSTRY
LOG TRANSPORTATION
MILP
SCHEDULING
VEHICLE ROUTING
topic FOREST INDUSTRY
LOG TRANSPORTATION
MILP
SCHEDULING
VEHICLE ROUTING
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.4
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv Transportation planning in forest industry is a challenging activity since it involves complex decisions about raw material allocation, vehicle routing and scheduling of trucks arrivals to both harvest areas and the plants. In the Argentine context, specifically in the Argentinean Northeast (NEA) region, the forest industry plays essential role for the economic development and, among the included activities, the transportation is the key element considering the volumes that must be moved and the distances to be traveled. Therefore, enhancing efficiency in the transportation activity improves significantly the performance of this industry. In this work, a Mixed Integer Linear Programming (MILP) model is presented, where raw material allocation, vehicle routing and scheduling of trucks arrivals are simultaneously addressed. Since the resolution times of the proposed integrated MILP model are prohibitive for large instances, a hierarchical approach is also presented. The considered decomposition approach involves two stages: in the first phase, the raw material allocation and vehicle routing problems are solved through a MILP model, while in the second phase, fixing the route for each truck according to the results of the previous step, the scheduling of truck arrivals to both the harvest areas and the plants is solved through a new MILP model. The obtained results show that the proposed approach is very effective and could be easily applied in this industry.
Fil: Bordon, Maximiliano Ramon. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
Fil: Montagna, Jorge Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
Fil: Corsano, Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
description Transportation planning in forest industry is a challenging activity since it involves complex decisions about raw material allocation, vehicle routing and scheduling of trucks arrivals to both harvest areas and the plants. In the Argentine context, specifically in the Argentinean Northeast (NEA) region, the forest industry plays essential role for the economic development and, among the included activities, the transportation is the key element considering the volumes that must be moved and the distances to be traveled. Therefore, enhancing efficiency in the transportation activity improves significantly the performance of this industry. In this work, a Mixed Integer Linear Programming (MILP) model is presented, where raw material allocation, vehicle routing and scheduling of trucks arrivals are simultaneously addressed. Since the resolution times of the proposed integrated MILP model are prohibitive for large instances, a hierarchical approach is also presented. The considered decomposition approach involves two stages: in the first phase, the raw material allocation and vehicle routing problems are solved through a MILP model, while in the second phase, fixing the route for each truck according to the results of the previous step, the scheduling of truck arrivals to both the harvest areas and the plants is solved through a new MILP model. The obtained results show that the proposed approach is very effective and could be easily applied in this industry.
publishDate 2020
dc.date.none.fl_str_mv 2020-09
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/11336/136171
Bordon, Maximiliano Ramon; Montagna, Jorge Marcelo; Corsano, Gabriela; Mixed integer linear programming approaches for solving the raw material allocation, routing and scheduling problems in the forest industry; Growing Science; International Journal of Industrial Engineering Computations; 11; 4; 9-2020; 525-548
1923-2926
1923-2934
CONICET Digital
CONICET
url http://hdl.handle.net/11336/136171
identifier_str_mv Bordon, Maximiliano Ramon; Montagna, Jorge Marcelo; Corsano, Gabriela; Mixed integer linear programming approaches for solving the raw material allocation, routing and scheduling problems in the forest industry; Growing Science; International Journal of Industrial Engineering Computations; 11; 4; 9-2020; 525-548
1923-2926
1923-2934
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://growingscience.com/beta/ijiec/4020-mixed-integer-linear-programming-approaches-for-solving-the-raw-material-allocation-routing-and-scheduling-problems-in-the-forest-industry.html
info:eu-repo/semantics/altIdentifier/doi/10.5267/j.ijiec.2020.5.001
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Growing Science
publisher.none.fl_str_mv Growing Science
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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