Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/102599
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dc.contributorDepartment of Civil and Environmental Engineeringen_US
dc.creatorChen, BYen_US
dc.creatorShi, Cen_US
dc.creatorZhang, Jen_US
dc.creatorLam, WHKen_US
dc.creatorLi, Qen_US
dc.creatorXiang, Sen_US
dc.date.accessioned2023-10-26T07:19:45Z-
dc.date.available2023-10-26T07:19:45Z-
dc.identifier.issn2168-0566en_US
dc.identifier.urihttp://hdl.handle.net/10397/102599-
dc.language.isoenen_US
dc.publisherTaylor & Francisen_US
dc.rights© 2016 Hong Kong Society for Transportation Studies Limiteden_US
dc.rightsThis is an Accepted Manuscript of an article published by Taylor & Francis in Transportmetrica B: Transport Dynamics on 13 Apr 2016 (published online), available at: http://www.tandfonline.com/10.1080/21680566.2016.1169953.en_US
dc.subjectMulti-criteria optimizationen_US
dc.subjectThe most reliable path problemen_US
dc.subjectTravel time reliabilityen_US
dc.titleMost reliable path-finding algorithm for maximizing on-time arrival probabilityen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage248en_US
dc.identifier.epage264en_US
dc.identifier.volume5en_US
dc.identifier.issue3en_US
dc.identifier.doi10.1080/21680566.2016.1169953en_US
dcterms.abstractFinding the most reliable path that maximizes the probability of on-time arrival is commonly encountered by travelers facing travel time uncertainties. However, few exact solution algorithms have been proposed in the literature to efficiently determine the most reliable path in large-scale road networks. In this study, a two-stage solution algorithm is proposed to exactly solve the most reliable path problem. In the first stage, the upper and lower bounds of on-time arrival probability are estimated. Dominance conditions and the monotonic property of the most reliable path problem are then established. In the second stage, the multi-criteria label-setting approach is utilized to efficiently determine the most reliable path. To illustrate the applicability of the proposed solution algorithm, a comprehensive case study is carried out using a real road network with stochastic travel times. The results of case study show that the proposed solution algorithm has a remarkable computational advantage over the existing multi-criteria label-correcting algorithm.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationTransportmetrica. B, Transport dynamics, 2017, v. 5, no. 3, p. 248-264en_US
dcterms.isPartOfTransportmetrica. B, Transport dynamicsen_US
dcterms.issued2017-
dc.identifier.scopus2-s2.0-84963614680-
dc.description.validate202310 bcchen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberCEE-2151-
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextNational Science Foundation of China; Research Institute of Sustainable Urban Development of the Hong Kong Polytechnic University; Shenzhen Scientific Research and Development Funding Program; Shenzhen Dedicated Funding of Strategic Emerging Industry Development Programen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS6634793-
dc.description.oaCategoryGreen (AAM)en_US
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