Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/101113
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dc.contributorDepartment of Civil and Environmental Engineeringen_US
dc.creatorChen, BYen_US
dc.creatorChen, XWen_US
dc.creatorChen, HPen_US
dc.creatorLam, WHKen_US
dc.date.accessioned2023-08-30T04:15:03Z-
dc.date.available2023-08-30T04:15:03Z-
dc.identifier.issn1366-5545en_US
dc.identifier.urihttp://hdl.handle.net/10397/101113-
dc.language.isoenen_US
dc.publisherPergamon Pressen_US
dc.rights© 2019 Elsevier Ltd. All rights reserved.en_US
dc.rights© 2019. 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., Chen, X. W., Chen, H. P., & Lam, W. H. (2020). Efficient algorithm for finding k shortest paths based on re-optimization technique. Transportation Research Part E: Logistics and Transportation Review, 133, 101819 is available at https://doi.org/10.1016/j.tre.2019.11.013.en_US
dc.subjectK shortest path problemen_US
dc.subjectLifelong planning A*en_US
dc.subjectRe-optimization techniqueen_US
dc.titleEfficient algorithm for finding K shortest paths based on re-optimization techniqueen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume133en_US
dc.identifier.doi10.1016/j.tre.2019.11.013en_US
dcterms.abstractThis study proposes an efficient deviation path algorithm for finding exactly k shortest simple paths without loops in road networks. The algorithm formulates the deviation path calculation process as repeated one-to-one searches for the shortest path in a dynamic network, where only a node and a link are restored at each search. Using this formulation, the proposed algorithm maintains and updates a single shortest path tree rooted at the destination. A re-optimization technique, lifelong planning A*, is incorporated into the algorithm to efficiently calculate each deviation path by reusing the shortest path tree generated at the previous search. To verify the efficiency of the proposed algorithm, computational experiments were conducted using several real road networks, and the results showed that the proposed algorithm performed significantly better than state-of-the-art algorithms.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationTransportation research. Part E, Logistics and transportation review, Jan. 2020, v. 133, 101819en_US
dcterms.isPartOfTransportation research. Part E, Logistics and transportation reviewen_US
dcterms.issued2020-01-
dc.identifier.scopus2-s2.0-85076456017-
dc.identifier.eissn1878-5794en_US
dc.identifier.artn101819en_US
dc.description.validate202308 bcchen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberCEE-1064-
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextNational Natural Science Foundation of China; Hong Kong Polytechnic University; National Basic Research Program of China (973 Program)en_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS19408035-
dc.description.oaCategoryGreen (AAM)en_US
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