Electric Vehicle Routing, Arc Routing, and Team Orienteering Problems in Sustainable Transportation
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 distribut...
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doaj-1616f8f29e934fb08b2ecc4b9d5f7c292021-08-26T13:43:33ZengMDPI AGEnergies1996-10732021-08-01145131513110.3390/en14165131Electric Vehicle Routing, Arc Routing, and Team Orienteering Problems in Sustainable TransportationLeandro do C. Martins0Rafael D. Tordecilla1Juliana Castaneda2Angel A. Juan3Javier Faulin4IN3–Computer Science Department, Universitat Oberta de Catalunya, 08018 Barcelona, SpainIN3–Computer Science Department, Universitat Oberta de Catalunya, 08018 Barcelona, SpainIN3–Computer Science Department, Universitat Oberta de Catalunya, 08018 Barcelona, SpainIN3–Computer Science Department, Universitat Oberta de Catalunya, 08018 Barcelona, SpainInstitute of Smart Cities, Department Statistics, Computer Sciences, and Mathematics, Public University of Navarre, 31006 Pamplona, SpainThe 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.https://www.mdpi.com/1996-1073/14/16/5131electric batteriesvehicle routing problemarc routing problemteam orienteering problem |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Leandro do C. Martins Rafael D. Tordecilla Juliana Castaneda Angel A. Juan Javier Faulin |
spellingShingle |
Leandro do C. Martins Rafael D. Tordecilla Juliana Castaneda Angel A. Juan Javier Faulin Electric Vehicle Routing, Arc Routing, and Team Orienteering Problems in Sustainable Transportation Energies electric batteries vehicle routing problem arc routing problem team orienteering problem |
author_facet |
Leandro do C. Martins Rafael D. Tordecilla Juliana Castaneda Angel A. Juan Javier Faulin |
author_sort |
Leandro do C. Martins |
title |
Electric Vehicle Routing, Arc Routing, and Team Orienteering Problems in Sustainable Transportation |
title_short |
Electric Vehicle Routing, Arc Routing, and Team Orienteering Problems in Sustainable Transportation |
title_full |
Electric Vehicle Routing, Arc Routing, and Team Orienteering Problems in Sustainable Transportation |
title_fullStr |
Electric Vehicle Routing, Arc Routing, and Team Orienteering Problems in Sustainable Transportation |
title_full_unstemmed |
Electric Vehicle Routing, Arc Routing, and Team Orienteering Problems in Sustainable Transportation |
title_sort |
electric vehicle routing, arc routing, and team orienteering problems in sustainable transportation |
publisher |
MDPI AG |
series |
Energies |
issn |
1996-1073 |
publishDate |
2021-08-01 |
description |
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. |
topic |
electric batteries vehicle routing problem arc routing problem team orienteering problem |
url |
https://www.mdpi.com/1996-1073/14/16/5131 |
work_keys_str_mv |
AT leandrodocmartins electricvehicleroutingarcroutingandteamorienteeringproblemsinsustainabletransportation AT rafaeldtordecilla electricvehicleroutingarcroutingandteamorienteeringproblemsinsustainabletransportation AT julianacastaneda electricvehicleroutingarcroutingandteamorienteeringproblemsinsustainabletransportation AT angelajuan electricvehicleroutingarcroutingandteamorienteeringproblemsinsustainabletransportation AT javierfaulin electricvehicleroutingarcroutingandteamorienteeringproblemsinsustainabletransportation |
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1721193666882568192 |