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...

Descripción completa

Detalles Bibliográficos
Autores: Reyes-Rubiano, Lorena Silvana, Ferone, Daniele, Juan Pérez, Ángel Alejandro, Faulín Fajardo, Javier
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2019
País:España
Institución:Universidad Pública de Navarra
Repositorio:Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
OAI Identifier:oai:academica-e.unavarra.es:2454/36261
Acceso en línea:https://hdl.handle.net/2454/36261
Access Level:acceso abierto
Palabra clave:Vehicle routing problem
Electric vehicles
Green transport and logistics
Smart cities
Simheuristics
Biased-randomized heuristics
id ES_bbc6fd620ea2f8ca52a6ce7e77011478
oai_identifier_str oai:academica-e.unavarra.es:2454/36261
network_acronym_str ES
network_name_str España
repository_id_str
spelling A simheuristic for routing electric vehicles with limited driving ranges and stochastic travel timesReyes-Rubiano, Lorena SilvanaFerone, DanieleJuan Pérez, Ángel AlejandroFaulín Fajardo, JavierVehicle routing problemElectric vehiclesGreen transport and logisticsSmart citiesSimheuristicsBiased-randomized heuristicsGreen 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.This work has been partially supported by the Spanish Ministry of Economy and Competitiveness (TRA2015-71883-REDT), and the Ibero-American Program for Science and Technology for Development (CYTED2014-515RT0489). Moreover, The authors appreciate the financial support of the Erasmus+ Program (2018-1-ES01-KA103-049767) as well as the support of the UPNA doctoral program.Institut d'Estadistica de Catalunya (Idescat)Institute of Smart Cities - ISCUniversidad Pública de Navarra / Nafarroako Unibertsitate Publikoa2019info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://hdl.handle.net/2454/36261reponame:Academica-e. Repositorio Institucional de la Universidad Pública de Navarrainstname:Universidad Pública de NavarraInglésinfo:eu-repo/grantAgreement/MINECO//TRA2015-71883-REDTinfo:eu-repo/grantAgreement/European Commission/ERASMUS+/2018-1-ES01-KA103-049767Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Spain (CC BY-NC-ND 3.0 ES)https://creativecommons.org/licenses/by-nc-nd/3.0/es/deed.en/info:eu-repo/semantics/openAccessoai:academica-e.unavarra.es:2454/362612026-06-17T12:41:47Z
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 Silvana
Vehicle routing problem
Electric vehicles
Green transport and logistics
Smart cities
Simheuristics
Biased-randomized heuristics
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 Silvana
Ferone, Daniele
Juan Pérez, Ángel Alejandro
Faulín Fajardo, Javier
author Reyes-Rubiano, Lorena Silvana
author_facet Reyes-Rubiano, Lorena Silvana
Ferone, Daniele
Juan Pérez, Ángel Alejandro
Faulín Fajardo, Javier
author_role author
author2 Ferone, Daniele
Juan Pérez, Ángel Alejandro
Faulín Fajardo, Javier
author2_role author
author
author
dc.contributor.none.fl_str_mv Institute of Smart Cities - ISC
Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
dc.subject.none.fl_str_mv Vehicle routing problem
Electric vehicles
Green transport and logistics
Smart cities
Simheuristics
Biased-randomized heuristics
topic Vehicle routing problem
Electric vehicles
Green transport and logistics
Smart cities
Simheuristics
Biased-randomized heuristics
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
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/2454/36261
url https://hdl.handle.net/2454/36261
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv info:eu-repo/grantAgreement/MINECO//TRA2015-71883-REDT
info:eu-repo/grantAgreement/European Commission/ERASMUS+/2018-1-ES01-KA103-049767
dc.rights.none.fl_str_mv Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Spain (CC BY-NC-ND 3.0 ES)
https://creativecommons.org/licenses/by-nc-nd/3.0/es/deed.en/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Spain (CC BY-NC-ND 3.0 ES)
https://creativecommons.org/licenses/by-nc-nd/3.0/es/deed.en/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Institut d'Estadistica de Catalunya (Idescat)
publisher.none.fl_str_mv Institut d'Estadistica de Catalunya (Idescat)
dc.source.none.fl_str_mv reponame:Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
instname:Universidad Pública de Navarra
instname_str Universidad Pública de Navarra
reponame_str Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
collection Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869418055518388224
score 15,81155

Similares en LA Referencia