Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/101294
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dc.contributorDepartment of Civil and Environmental Engineeringen_US
dc.creatorChen, BYen_US
dc.creatorLi, Qen_US
dc.creatorLam, WHKen_US
dc.date.accessioned2023-08-30T04:16:34Z-
dc.date.available2023-08-30T04:16:34Z-
dc.identifier.issn0191-2615en_US
dc.identifier.urihttp://hdl.handle.net/10397/101294-
dc.language.isoenen_US
dc.publisherPergamon Pressen_US
dc.rights© 2016 Elsevier Ltd. All rights reserved.en_US
dc.rights© 2016. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.rightsThe following publication Chen, B. Y., Li, Q., & Lam, W. H. (2016). Finding the k reliable shortest paths under travel time uncertainty. Transportation Research Part B: Methodological, 94, 189-203 is available at https://doi.org/10.1016/j.trb.2016.09.013.en_US
dc.subjectK reliable shortest paths problemen_US
dc.subjectReliabilityen_US
dc.subjectTravel time uncertaintyen_US
dc.titleFinding the K reliable shortest paths under travel time uncertaintyen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage189en_US
dc.identifier.epage203en_US
dc.identifier.volume94en_US
dc.identifier.doi10.1016/j.trb.2016.09.013en_US
dcterms.abstractThis paper investigates the problem of finding the K reliable shortest paths (KRSP) in stochastic networks under travel time uncertainty. The KRSP problem extends the classical K loopless shortest paths problem to the stochastic networks by explicitly considering travel time reliability. In this study, a deviation path approach is established for finding K α-reliable paths in stochastic networks. A deviation path algorithm is proposed to exactly solve the KRSP problem in large-scale networks. The A* technique is introduced to further improve the KRSP finding performance. A case study using real traffic information is performed to validate the proposed algorithm. The results indicate that the proposed algorithm can determine KRSP under various travel time reliability values within reasonable computational times. The introduced A* technique can significantly improve KRSP finding performance.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationTransportation research. Part B, Methodological, Dec. 2016, v. 94, p. 189-203en_US
dcterms.isPartOfTransportation research. Part B, Methodologicalen_US
dcterms.issued2016-12-
dc.identifier.scopus2-s2.0-84990026500-
dc.identifier.eissn1879-2367en_US
dc.description.validate202308 bcchen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberCEE-2408-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextNational Natural Science Foundation of China; Hong Kong Polytechnic University; Research Institute for Sustainable Urban Development, Hong Kong Polytechnic Universityen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS6683847-
dc.description.oaCategoryGreen (AAM)en_US
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