An iterative solution approach for truck routing and scheduling in the forest industry
- Autores
- Bordón, Maximiliano; Montagna, Jorge Marcelo; Corsano, Gabriela
- Año de publicación
- 2018
- Idioma
- inglés
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- Log transportation in forest industry is a resource-intensive operation and represents a great challenge for logistic planners. Several trips must be generated in order to satisfy plants demand; in addition, trucks arrivals at each plant must be considered in order to avoid unproductive waiting times. In the Argentine context, specifically in the Argentinean Northeast (NEA) region, these activities represent the main sustenance of the regional economies, so enhancing efficiency in the transport operation would represent a considerable improvement for these economies. In this work, an iterative solution approach for the truck routing and scheduling problems is presented. The proposed strategy involves two stages which are iteratively solved: product allocation, trip composition and truck routing problems are first solved through a Mixed-Integer Linear Programming model (MILP), while in the second stage, fixing the route for each truck according to the results of the previous step, a MILP model for the scheduling of truck arrivals at plants is considered. If no feasible solution for the scheduling problem is obtained, then an integer cut is applied in order to exclude from the search space truck routes already explored in previous iterations. The solution approach is tested in a case study representative of the Argentine context and conclusions are detailed.
Sociedad Argentina de Informática e Investigación Operativa - Materia
-
Ciencias Informáticas
vehicle routing
vehicle scheduling
forest
MILP - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-sa/3.0/
- Repositorio
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/71886
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An iterative solution approach for truck routing and scheduling in the forest industryBordón, MaximilianoMontagna, Jorge MarceloCorsano, GabrielaCiencias Informáticasvehicle routingvehicle schedulingforestMILPLog transportation in forest industry is a resource-intensive operation and represents a great challenge for logistic planners. Several trips must be generated in order to satisfy plants demand; in addition, trucks arrivals at each plant must be considered in order to avoid unproductive waiting times. In the Argentine context, specifically in the Argentinean Northeast (NEA) region, these activities represent the main sustenance of the regional economies, so enhancing efficiency in the transport operation would represent a considerable improvement for these economies. In this work, an iterative solution approach for the truck routing and scheduling problems is presented. The proposed strategy involves two stages which are iteratively solved: product allocation, trip composition and truck routing problems are first solved through a Mixed-Integer Linear Programming model (MILP), while in the second stage, fixing the route for each truck according to the results of the previous step, a MILP model for the scheduling of truck arrivals at plants is considered. If no feasible solution for the scheduling problem is obtained, then an integer cut is applied in order to exclude from the search space truck routes already explored in previous iterations. The solution approach is tested in a case study representative of the Argentine context and conclusions are detailed.Sociedad Argentina de Informática e Investigación Operativa2018-09info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf41-54http://sedici.unlp.edu.ar/handle/10915/71886enginfo:eu-repo/semantics/altIdentifier/url/http://47jaiio.sadio.org.ar/sites/default/files/SIIIO-04.pdfinfo:eu-repo/semantics/altIdentifier/issn/2618-3277info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-sa/3.0/Creative Commons Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-15T11:03:41Zoai:sedici.unlp.edu.ar:10915/71886Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-15 11:03:41.578SEDICI (UNLP) - Universidad Nacional de La Platafalse |
dc.title.none.fl_str_mv |
An iterative solution approach for truck routing and scheduling in the forest industry |
title |
An iterative solution approach for truck routing and scheduling in the forest industry |
spellingShingle |
An iterative solution approach for truck routing and scheduling in the forest industry Bordón, Maximiliano Ciencias Informáticas vehicle routing vehicle scheduling forest MILP |
title_short |
An iterative solution approach for truck routing and scheduling in the forest industry |
title_full |
An iterative solution approach for truck routing and scheduling in the forest industry |
title_fullStr |
An iterative solution approach for truck routing and scheduling in the forest industry |
title_full_unstemmed |
An iterative solution approach for truck routing and scheduling in the forest industry |
title_sort |
An iterative solution approach for truck routing and scheduling in the forest industry |
dc.creator.none.fl_str_mv |
Bordón, Maximiliano Montagna, Jorge Marcelo Corsano, Gabriela |
author |
Bordón, Maximiliano |
author_facet |
Bordón, Maximiliano Montagna, Jorge Marcelo Corsano, Gabriela |
author_role |
author |
author2 |
Montagna, Jorge Marcelo Corsano, Gabriela |
author2_role |
author author |
dc.subject.none.fl_str_mv |
Ciencias Informáticas vehicle routing vehicle scheduling forest MILP |
topic |
Ciencias Informáticas vehicle routing vehicle scheduling forest MILP |
dc.description.none.fl_txt_mv |
Log transportation in forest industry is a resource-intensive operation and represents a great challenge for logistic planners. Several trips must be generated in order to satisfy plants demand; in addition, trucks arrivals at each plant must be considered in order to avoid unproductive waiting times. In the Argentine context, specifically in the Argentinean Northeast (NEA) region, these activities represent the main sustenance of the regional economies, so enhancing efficiency in the transport operation would represent a considerable improvement for these economies. In this work, an iterative solution approach for the truck routing and scheduling problems is presented. The proposed strategy involves two stages which are iteratively solved: product allocation, trip composition and truck routing problems are first solved through a Mixed-Integer Linear Programming model (MILP), while in the second stage, fixing the route for each truck according to the results of the previous step, a MILP model for the scheduling of truck arrivals at plants is considered. If no feasible solution for the scheduling problem is obtained, then an integer cut is applied in order to exclude from the search space truck routes already explored in previous iterations. The solution approach is tested in a case study representative of the Argentine context and conclusions are detailed. Sociedad Argentina de Informática e Investigación Operativa |
description |
Log transportation in forest industry is a resource-intensive operation and represents a great challenge for logistic planners. Several trips must be generated in order to satisfy plants demand; in addition, trucks arrivals at each plant must be considered in order to avoid unproductive waiting times. In the Argentine context, specifically in the Argentinean Northeast (NEA) region, these activities represent the main sustenance of the regional economies, so enhancing efficiency in the transport operation would represent a considerable improvement for these economies. In this work, an iterative solution approach for the truck routing and scheduling problems is presented. The proposed strategy involves two stages which are iteratively solved: product allocation, trip composition and truck routing problems are first solved through a Mixed-Integer Linear Programming model (MILP), while in the second stage, fixing the route for each truck according to the results of the previous step, a MILP model for the scheduling of truck arrivals at plants is considered. If no feasible solution for the scheduling problem is obtained, then an integer cut is applied in order to exclude from the search space truck routes already explored in previous iterations. The solution approach is tested in a case study representative of the Argentine context and conclusions are detailed. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-09 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/publishedVersion Objeto de conferencia http://purl.org/coar/resource_type/c_5794 info:ar-repo/semantics/documentoDeConferencia |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://sedici.unlp.edu.ar/handle/10915/71886 |
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http://sedici.unlp.edu.ar/handle/10915/71886 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
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openAccess |
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http://creativecommons.org/licenses/by-sa/3.0/ Creative Commons Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0) |
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