Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/95448
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dc.contributorDepartment of Civil and Environmental Engineeringen_US
dc.creatorChen, XWen_US
dc.creatorChen, BYen_US
dc.creatorLam, WHKen_US
dc.creatorTam, MLen_US
dc.creatorMa, Wen_US
dc.date.accessioned2022-09-19T02:02:03Z-
dc.date.available2022-09-19T02:02:03Z-
dc.identifier.issn0957-4174en_US
dc.identifier.urihttp://hdl.handle.net/10397/95448-
dc.language.isoenen_US
dc.publisherPergamon Pressen_US
dc.rights© 2021 Elsevier Ltd. All rights reserved.en_US
dc.rights© 2021. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/.en_US
dc.rightsThe following publication Chen, X.-W., et al. (2021). "A bi-objective reliable path-finding algorithm for battery electric vehicle routing." Expert Systems with Applications 182: 115228 is available at https://dx.doi.org/10.1016/j.eswa.2021.115228.en_US
dc.subjectBi-objective path findingen_US
dc.subjectEnergy consumption reliabilityen_US
dc.subjectNetwork uncertaintiesen_US
dc.subjectTravel time reliabilityen_US
dc.titleA bi-objective reliable path-finding algorithm for battery electric vehicle routingen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume182en_US
dc.identifier.doi10.1016/j.eswa.2021.115228en_US
dcterms.abstractThis paper proposes a bi-objective reliable path-finding algorithm for routing battery electric vehicles on a road network, with vehicles’ energy consumption uncertainty and travel time uncertainty. A bi-objective stochastic optimization problem is proposed and formulated to simultaneously maximize energy consumption reliability (ECR) and travel time reliability (TTR). ECR is defined as the probability of finishing a trip without exhausting a given battery energy budget, while TTR is the on-time arrival probability with the travel time budget. In this study, the proposed optimization problem is decomposed into two sub-problems: (1) finding K most reliable paths for maximizing the TTR objective and (2) finding the most reliable path for optimizing the ECR objective. Then, a novel ranking algorithm is proposed to exactly solve the formulated optimization problem. A case study is carried out on Hong Kong's road network to demonstrate the efficacy and efficiency of the proposed algorithm for real-world applications.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationExpert systems with applications, 11 Nov. 2021, v. 182, 115228en_US
dcterms.isPartOfExpert systems with applicationsen_US
dcterms.issued2021-11-11-
dc.identifier.scopus2-s2.0-85106465326-
dc.identifier.eissn1873-6793en_US
dc.identifier.artn115228en_US
dc.description.validate202209 bcfcen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberCEE-0082-
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextNational Key Research and Development Program; Dean's Reserve of the Hong Kong PolyU; NSF (Hubei Province)en_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS52136207-
dc.description.oaCategoryGreen (AAM)en_US
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