Heuristics for dynamic and stochastic routing in industrial shipping

Maritime transportation plays a central role in international trade, being responsible for the majority of long-distance shipments in terms of volume. One of the key aspects in the planning of maritime transportation systems is the routing of ships. While static and deterministic vehicle routing pro...

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Detalles Bibliográficos
Autores: Tirado Domínguez, Gregorio, Hvattum, Lars Magnus, Fagerholt, Kjetil, Cordeau, Jean-Francois
Tipo de recurso: artículo
Fecha de publicación:2013
País:España
Institución:Universidad Complutense de Madrid (UCM)
Repositorio:Docta Complutense
Idioma:inglés
OAI Identifier:oai:docta.ucm.es:20.500.14352/33262
Acceso en línea:https://hdl.handle.net/20.500.14352/33262
Access Level:acceso abierto
Palabra clave:519.876.5
Maritime transportation
Simulation
Tabu search
Investigación operativa (Matemáticas)
1207 Investigación Operativa
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oai_identifier_str oai:docta.ucm.es:20.500.14352/33262
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repository_id_str
spelling Heuristics for dynamic and stochastic routing in industrial shippingTirado Domínguez, GregorioHvattum, Lars MagnusFagerholt, KjetilCordeau, Jean-Francois519.876.5Maritime transportationSimulationTabu searchInvestigación operativa (Matemáticas)1207 Investigación OperativaMaritime transportation plays a central role in international trade, being responsible for the majority of long-distance shipments in terms of volume. One of the key aspects in the planning of maritime transportation systems is the routing of ships. While static and deterministic vehicle routing problems have been extensively studied in the last decades and can now be solved effectively with metaheuristics, many industrial applications are both dynamic and stochastic. In this spirit, this paper addresses a dynamic and stochastic maritime transportation problem arising in industrial shipping. Three heuristics adapted to this problem are considered and their performance in minimizing transportation costs is assessed. Extensive computational experiments show that the use of stochastic information within the proposed solution methods yields average cost savings of 2.5% on a set of realistic test instances.Pergamon-ElsevierUniversidad Complutense de Madrid20132013-01-0120132013-01-01journal articlehttp://purl.org/coar/resource_type/c_6501info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/20.500.14352/33262reponame:Docta Complutenseinstname:Universidad Complutense de Madrid (UCM)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:docta.ucm.es:20.500.14352/332622026-06-02T12:44:21Z
dc.title.none.fl_str_mv Heuristics for dynamic and stochastic routing in industrial shipping
title Heuristics for dynamic and stochastic routing in industrial shipping
spellingShingle Heuristics for dynamic and stochastic routing in industrial shipping
Tirado Domínguez, Gregorio
519.876.5
Maritime transportation
Simulation
Tabu search
Investigación operativa (Matemáticas)
1207 Investigación Operativa
title_short Heuristics for dynamic and stochastic routing in industrial shipping
title_full Heuristics for dynamic and stochastic routing in industrial shipping
title_fullStr Heuristics for dynamic and stochastic routing in industrial shipping
title_full_unstemmed Heuristics for dynamic and stochastic routing in industrial shipping
title_sort Heuristics for dynamic and stochastic routing in industrial shipping
dc.creator.none.fl_str_mv Tirado Domínguez, Gregorio
Hvattum, Lars Magnus
Fagerholt, Kjetil
Cordeau, Jean-Francois
author Tirado Domínguez, Gregorio
author_facet Tirado Domínguez, Gregorio
Hvattum, Lars Magnus
Fagerholt, Kjetil
Cordeau, Jean-Francois
author_role author
author2 Hvattum, Lars Magnus
Fagerholt, Kjetil
Cordeau, Jean-Francois
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidad Complutense de Madrid
dc.subject.none.fl_str_mv 519.876.5
Maritime transportation
Simulation
Tabu search
Investigación operativa (Matemáticas)
1207 Investigación Operativa
topic 519.876.5
Maritime transportation
Simulation
Tabu search
Investigación operativa (Matemáticas)
1207 Investigación Operativa
description Maritime transportation plays a central role in international trade, being responsible for the majority of long-distance shipments in terms of volume. One of the key aspects in the planning of maritime transportation systems is the routing of ships. While static and deterministic vehicle routing problems have been extensively studied in the last decades and can now be solved effectively with metaheuristics, many industrial applications are both dynamic and stochastic. In this spirit, this paper addresses a dynamic and stochastic maritime transportation problem arising in industrial shipping. Three heuristics adapted to this problem are considered and their performance in minimizing transportation costs is assessed. Extensive computational experiments show that the use of stochastic information within the proposed solution methods yields average cost savings of 2.5% on a set of realistic test instances.
publishDate 2013
dc.date.none.fl_str_mv 2013
2013-01-01
2013
2013-01-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/20.500.14352/33262
url https://hdl.handle.net/20.500.14352/33262
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Pergamon-Elsevier
publisher.none.fl_str_mv Pergamon-Elsevier
dc.source.none.fl_str_mv reponame:Docta Complutense
instname:Universidad Complutense de Madrid (UCM)
instname_str Universidad Complutense de Madrid (UCM)
reponame_str Docta Complutense
collection Docta Complutense
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,300719

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