A simheuristic for routing electric vehicles with limited driving ranges and stochastic travel times

Green transportation is becoming relevant in the context of smart cities, where the use of electric vehicles represents a promising strategy to support sustainability policies. However the use of electric vehicles shows some drawbacks as well, such as their limited driving-range capacity. This paper...

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Detalles Bibliográficos
Autores: Reyes-Rubiano, Lorena, Ferone, Daniele|||0000-0003-4696-7826, Juan, Angel A., Faulin, Javier
Tipo de recurso: artículo
Fecha de publicación:2019
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/178329
Acceso en línea:https://hdl.handle.net/2117/178329
Access Level:acceso abierto
Palabra clave:Vehicle routing problem
electric vehicles
green transport and logistics
smart cities
simheuristics
biased-randomized heuristics
Classificació AMS::90 Operations research, mathematical programming::90B Operations research and management science
Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica
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spelling A simheuristic for routing electric vehicles with limited driving ranges and stochastic travel timesReyes-Rubiano, LorenaFerone, Daniele|||0000-0003-4696-7826Juan, Angel A.Faulin, JavierVehicle routing problemelectric vehiclesgreen transport and logisticssmart citiessimheuristicsbiased-randomized heuristicsClassificació AMS::90 Operations research, mathematical programming::90B Operations research and management scienceÀrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàticaGreen transportation is becoming relevant in the context of smart cities, where the use of electric vehicles represents a promising strategy to support sustainability policies. However the use of electric vehicles shows some drawbacks as well, such as their limited driving-range capacity. This paper analyses a realistic vehicle routing problem in which both driving-range constraints and stochastic travel times are considered. Thus, the main goal is to minimize the expected time-based cost required to complete the freight distribution plan. In order to design reliable Routing plans, a simheuristic algorithm is proposed. It combines Monte Carlo simulation with a multi-start metaheuristic, which also employs biased-randomization techniques. By including simulation, simheuristics extend the capabilities of metaheuristics to deal with stochastic problems. A series of computational experiments are performed to test our solving approach as well as to analyse the effect of uncertainty on the routing plans.Peer ReviewedInstitut d'Estadística de Catalunya20192019-06-1120202020-02-21journal articlehttp://purl.org/coar/resource_type/c_6501NAhttp://purl.org/coar/version/c_be7fb7dd8ff6fe43info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/178329reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution-NonCommercial-NoDerivs 3.0 Spainhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/1783292026-05-27T15:37:01Z
dc.title.none.fl_str_mv A simheuristic for routing electric vehicles with limited driving ranges and stochastic travel times
title A simheuristic for routing electric vehicles with limited driving ranges and stochastic travel times
spellingShingle A simheuristic for routing electric vehicles with limited driving ranges and stochastic travel times
Reyes-Rubiano, Lorena
Vehicle routing problem
electric vehicles
green transport and logistics
smart cities
simheuristics
biased-randomized heuristics
Classificació AMS::90 Operations research, mathematical programming::90B Operations research and management science
Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica
title_short A simheuristic for routing electric vehicles with limited driving ranges and stochastic travel times
title_full A simheuristic for routing electric vehicles with limited driving ranges and stochastic travel times
title_fullStr A simheuristic for routing electric vehicles with limited driving ranges and stochastic travel times
title_full_unstemmed A simheuristic for routing electric vehicles with limited driving ranges and stochastic travel times
title_sort A simheuristic for routing electric vehicles with limited driving ranges and stochastic travel times
dc.creator.none.fl_str_mv Reyes-Rubiano, Lorena
Ferone, Daniele|||0000-0003-4696-7826
Juan, Angel A.
Faulin, Javier
author Reyes-Rubiano, Lorena
author_facet Reyes-Rubiano, Lorena
Ferone, Daniele|||0000-0003-4696-7826
Juan, Angel A.
Faulin, Javier
author_role author
author2 Ferone, Daniele|||0000-0003-4696-7826
Juan, Angel A.
Faulin, Javier
author2_role author
author
author
dc.subject.none.fl_str_mv Vehicle routing problem
electric vehicles
green transport and logistics
smart cities
simheuristics
biased-randomized heuristics
Classificació AMS::90 Operations research, mathematical programming::90B Operations research and management science
Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica
topic Vehicle routing problem
electric vehicles
green transport and logistics
smart cities
simheuristics
biased-randomized heuristics
Classificació AMS::90 Operations research, mathematical programming::90B Operations research and management science
Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica
description Green transportation is becoming relevant in the context of smart cities, where the use of electric vehicles represents a promising strategy to support sustainability policies. However the use of electric vehicles shows some drawbacks as well, such as their limited driving-range capacity. This paper analyses a realistic vehicle routing problem in which both driving-range constraints and stochastic travel times are considered. Thus, the main goal is to minimize the expected time-based cost required to complete the freight distribution plan. In order to design reliable Routing plans, a simheuristic algorithm is proposed. It combines Monte Carlo simulation with a multi-start metaheuristic, which also employs biased-randomization techniques. By including simulation, simheuristics extend the capabilities of metaheuristics to deal with stochastic problems. A series of computational experiments are performed to test our solving approach as well as to analyse the effect of uncertainty on the routing plans.
publishDate 2019
dc.date.none.fl_str_mv 2019
2019-06-11
2020
2020-02-21
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
NA
http://purl.org/coar/version/c_be7fb7dd8ff6fe43
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/178329
url https://hdl.handle.net/2117/178329
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
Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
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
Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Institut d'Estadística de Catalunya
publisher.none.fl_str_mv Institut d'Estadística de Catalunya
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.300719

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