Electric vehicle routing, arc routing, and team orienteering problems in sustainable transportation

Date

2021

Authors

Carmo Martins, Leandro do
Tordecilla, Rafael D.
Castaneda, Juliana
Juan, Ángel A.

Director

Publisher

MDPI
Acceso abierto / Sarbide irekia
Artículo / Artikulua
Versión publicada / Argitaratu den bertsioa

Project identifier

  • European Commission/Horizon 2020 Framework Programme/731884/ openaire
  • AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-111100RB-C22/ES/ recolecta
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Abstract

The increasing use of electric vehicles in road and air transportation, especially in last-mile delivery and city mobility, raises new operational challenges due to the limited capacity of electric batteries. These limitations impose additional driving range constraints when optimizing the distribution and mobility plans. During the last years, several researchers from the Computer Science, Artificial Intelligence, and Operations Research communities have been developing optimization, simulation, and machine learning approaches that aim at generating efficient and sustainable routing plans for hybrid fleets, including both electric and internal combustion engine vehicles. After contextualizing the relevance of electric vehicles in promoting sustainable transportation practices, this paper reviews the existing work in the field of electric vehicle routing problems. In particular, we focus on articles related to the well-known vehicle routing, arc routing, and team orienteering problems. The review is followed by numerical examples that illustrate the gains that can be obtained by employing optimization methods in the aforementioned field. Finally, several research opportunities are highlighted.

Description

Keywords

Electric batteries, Vehicle routing problem, Arc routing problem, Team orienteering problem

Department

Estatistika, Informatika eta Matematika / Institute of Smart Cities - ISC / Estadística, Informática y Matemáticas

Faculty/School

Degree

Doctorate program

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© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.

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