File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: A Time-Dependent Electric Vehicle Routing Problem With Congestion Tolls

TitleA Time-Dependent Electric Vehicle Routing Problem With Congestion Tolls
Authors
KeywordsBatteries
Routing
Roads
Electric vehicles
Adaptation models
Issue Date2020
PublisherIEEE. The Journal's web site is located at https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=17
Citation
IEEE Transactions on Engineering Management, 2020, Epub 2020-01-01, p. 1-13 How to Cite?
AbstractScheduling the recharging of electric vehicle fleets under different scenarios is an important but open problem. One important scenario is that vehicles travel at different speeds in different periods since traffic congestion is common in urban areas nowadays. Therefore, in this article, a novel time-dependent electric vehicle routing problem with congestion tolls is proposed. If a vehicle enters a peak period, a fixed congestion toll needs to be paid in this problem. A mixed integer linear programming model is established and an adaptive large neighborhood search (ALNS) heuristic is designed to solve the model. The model and solving method are validated and evaluated extensively with benchmark instances. Results indicate that a certain level of congestion tolls could prevent vehicles from entering peak periods and relieve road congestions significantly. Furthermore, the ALNS heuristic could provide much better solutions for the problem than typical optimization software, such as Gurobi, in much shorter running time.
Persistent Identifierhttp://hdl.handle.net/10722/287149
ISSN
2023 Impact Factor: 4.6
2023 SCImago Journal Rankings: 1.201
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorZhang, R-
dc.contributor.authorGuo, J-
dc.contributor.authorWang, J-
dc.date.accessioned2020-09-22T02:56:31Z-
dc.date.available2020-09-22T02:56:31Z-
dc.date.issued2020-
dc.identifier.citationIEEE Transactions on Engineering Management, 2020, Epub 2020-01-01, p. 1-13-
dc.identifier.issn0018-9391-
dc.identifier.urihttp://hdl.handle.net/10722/287149-
dc.description.abstractScheduling the recharging of electric vehicle fleets under different scenarios is an important but open problem. One important scenario is that vehicles travel at different speeds in different periods since traffic congestion is common in urban areas nowadays. Therefore, in this article, a novel time-dependent electric vehicle routing problem with congestion tolls is proposed. If a vehicle enters a peak period, a fixed congestion toll needs to be paid in this problem. A mixed integer linear programming model is established and an adaptive large neighborhood search (ALNS) heuristic is designed to solve the model. The model and solving method are validated and evaluated extensively with benchmark instances. Results indicate that a certain level of congestion tolls could prevent vehicles from entering peak periods and relieve road congestions significantly. Furthermore, the ALNS heuristic could provide much better solutions for the problem than typical optimization software, such as Gurobi, in much shorter running time.-
dc.languageeng-
dc.publisherIEEE. The Journal's web site is located at https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=17-
dc.relation.ispartofIEEE Transactions on Engineering Management-
dc.rightsIEEE Transactions on Engineering Management. Copyright © IEEE.-
dc.rights©20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.-
dc.subjectBatteries-
dc.subjectRouting-
dc.subjectRoads-
dc.subjectElectric vehicles-
dc.subjectAdaptation models-
dc.titleA Time-Dependent Electric Vehicle Routing Problem With Congestion Tolls-
dc.typeArticle-
dc.identifier.emailWang, J: jwwang@hku.hk-
dc.identifier.authorityWang, J=rp01888-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/TEM.2019.2959701-
dc.identifier.scopuseid_2-s2.0-85077369803-
dc.identifier.hkuros314572-
dc.identifier.volumeEpub 2020-01-01-
dc.identifier.spage1-
dc.identifier.epage13-
dc.identifier.isiWOS:000809409400008-
dc.publisher.placeUnited States-
dc.identifier.issnl0018-9391-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats