Electric Vehicle Routing Model for Last-mile Logistics in Cities with Steep Streets

Autores
García, Emilio; Torres, Luis M.; Miranda Bront, Juan José
Año de publicación
2024
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
The Quito local government aims to establish a low-emission zone in the city’s historic center. A key focus is the shift to eco-friendly transportation for last-mile logistics, including electric cargo bikes and other types of light electric vehicles (LEVs). Our research delves into integer programming models to optimize the vehicle routes. We address a variation of the electric vehicle routing problem (EVRP), factoring in vehicle load and street slope for battery consumption and travel times. Moreover, we consider the existence of multiple paths between each pair of customers, which vary in distance and slope, yielding different travel times and battery consumption values. For instance, some paths may have small travel times but require high battery consumption, while other paths may have longer travel times and require less battery consumption. The problem is formulated on a customer multigraph that has one node for each customer and depot, and where parallel arcs are used to represent efficient paths in the original network. Road selection is carried out as part of the vehicle routing. This talk highlights findings on modeling strategies and reports some computational results to examine the impact of some model parameters upon the optimal solutions.
Sociedad Argentina de Informática e Investigación Operativa
Materia
Ciencias Informáticas
Integer linear programming
Electric Vehicle Routing Problem
Steep Slope
Multiple Paths
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/177368
Acceder
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spelling Electric Vehicle Routing Model for Last-mile Logistics in Cities with Steep StreetsGarcía, EmilioTorres, Luis M.Miranda Bront, Juan JoséCiencias InformáticasInteger linear programmingElectric Vehicle Routing ProblemSteep SlopeMultiple PathsThe Quito local government aims to establish a low-emission zone in the city’s historic center. A key focus is the shift to eco-friendly transportation for last-mile logistics, including electric cargo bikes and other types of light electric vehicles (LEVs). Our research delves into integer programming models to optimize the vehicle routes. We address a variation of the electric vehicle routing problem (EVRP), factoring in vehicle load and street slope for battery consumption and travel times. Moreover, we consider the existence of multiple paths between each pair of customers, which vary in distance and slope, yielding different travel times and battery consumption values. For instance, some paths may have small travel times but require high battery consumption, while other paths may have longer travel times and require less battery consumption. The problem is formulated on a customer multigraph that has one node for each customer and depot, and where parallel arcs are used to represent efficient paths in the original network. Road selection is carried out as part of the vehicle routing. This talk highlights findings on modeling strategies and reports some computational results to examine the impact of some model parameters upon the optimal solutions.Sociedad Argentina de Informática e Investigación Operativa2024-08info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf426-429http://sedici.unlp.edu.ar/handle/10915/177368enginfo:eu-repo/semantics/altIdentifier/url/https://revistas.unlp.edu.ar/JAIIO/article/view/18006info:eu-repo/semantics/altIdentifier/issn/2451-7496info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:47:48Zoai:sedici.unlp.edu.ar:10915/177368Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:47:48.332SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Electric Vehicle Routing Model for Last-mile Logistics in Cities with Steep Streets
title Electric Vehicle Routing Model for Last-mile Logistics in Cities with Steep Streets
spellingShingle Electric Vehicle Routing Model for Last-mile Logistics in Cities with Steep Streets
García, Emilio
Ciencias Informáticas
Integer linear programming
Electric Vehicle Routing Problem
Steep Slope
Multiple Paths
title_short Electric Vehicle Routing Model for Last-mile Logistics in Cities with Steep Streets
title_full Electric Vehicle Routing Model for Last-mile Logistics in Cities with Steep Streets
title_fullStr Electric Vehicle Routing Model for Last-mile Logistics in Cities with Steep Streets
title_full_unstemmed Electric Vehicle Routing Model for Last-mile Logistics in Cities with Steep Streets
title_sort Electric Vehicle Routing Model for Last-mile Logistics in Cities with Steep Streets
dc.creator.none.fl_str_mv García, Emilio
Torres, Luis M.
Miranda Bront, Juan José
author García, Emilio
author_facet García, Emilio
Torres, Luis M.
Miranda Bront, Juan José
author_role author
author2 Torres, Luis M.
Miranda Bront, Juan José
author2_role author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Integer linear programming
Electric Vehicle Routing Problem
Steep Slope
Multiple Paths
topic Ciencias Informáticas
Integer linear programming
Electric Vehicle Routing Problem
Steep Slope
Multiple Paths
dc.description.none.fl_txt_mv The Quito local government aims to establish a low-emission zone in the city’s historic center. A key focus is the shift to eco-friendly transportation for last-mile logistics, including electric cargo bikes and other types of light electric vehicles (LEVs). Our research delves into integer programming models to optimize the vehicle routes. We address a variation of the electric vehicle routing problem (EVRP), factoring in vehicle load and street slope for battery consumption and travel times. Moreover, we consider the existence of multiple paths between each pair of customers, which vary in distance and slope, yielding different travel times and battery consumption values. For instance, some paths may have small travel times but require high battery consumption, while other paths may have longer travel times and require less battery consumption. The problem is formulated on a customer multigraph that has one node for each customer and depot, and where parallel arcs are used to represent efficient paths in the original network. Road selection is carried out as part of the vehicle routing. This talk highlights findings on modeling strategies and reports some computational results to examine the impact of some model parameters upon the optimal solutions.
Sociedad Argentina de Informática e Investigación Operativa
description The Quito local government aims to establish a low-emission zone in the city’s historic center. A key focus is the shift to eco-friendly transportation for last-mile logistics, including electric cargo bikes and other types of light electric vehicles (LEVs). Our research delves into integer programming models to optimize the vehicle routes. We address a variation of the electric vehicle routing problem (EVRP), factoring in vehicle load and street slope for battery consumption and travel times. Moreover, we consider the existence of multiple paths between each pair of customers, which vary in distance and slope, yielding different travel times and battery consumption values. For instance, some paths may have small travel times but require high battery consumption, while other paths may have longer travel times and require less battery consumption. The problem is formulated on a customer multigraph that has one node for each customer and depot, and where parallel arcs are used to represent efficient paths in the original network. Road selection is carried out as part of the vehicle routing. This talk highlights findings on modeling strategies and reports some computational results to examine the impact of some model parameters upon the optimal solutions.
publishDate 2024
dc.date.none.fl_str_mv 2024-08
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
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dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/177368
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dc.language.none.fl_str_mv eng
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info:eu-repo/semantics/altIdentifier/issn/2451-7496
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
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Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
426-429
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