Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/106859
DC FieldValueLanguage
dc.contributorDepartment of Logistics and Maritime Studiesen_US
dc.creatorSu, Een_US
dc.creatorQin, Hen_US
dc.creatorLi, Jen_US
dc.creatorPan, Ken_US
dc.date.accessioned2024-06-06T06:06:00Z-
dc.date.available2024-06-06T06:06:00Z-
dc.identifier.issn0191-2615en_US
dc.identifier.urihttp://hdl.handle.net/10397/106859-
dc.language.isoenen_US
dc.publisherElsevier Ltden_US
dc.subjectBranch-and-price-and-cuten_US
dc.subjectCrowdsourced deliveryen_US
dc.subjectPickup and deliveryen_US
dc.subjectTransshipment facilitiesen_US
dc.subjectVehicle routingen_US
dc.titleAn exact algorithm for the pickup and delivery problem with crowdsourced bids and transshipmenten_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume177en_US
dc.identifier.doi10.1016/j.trb.2023.102831en_US
dcterms.abstractThis paper addresses a pickup and delivery problem with crowdsourced bids and transshipment (PDPCBT) in last-mile delivery, where all requests can be satisfied by either using the own vehicle fleet or outsourcing with a small compensation to crowdshippers through transshipment facilities. The crowdshippers show their willingness to deliver by submitting bids to the e-commerce company. To minimize both the travel cost of vehicles and the compensation of crowdshippers, the routes of vehicles and the selection of bids need to be optimized simultaneously. We formulate the PDPCBT into an arc-based formulation and a route-based formulation, where the latter is strengthened by the subset row inequalities. Based on the route-based formulation, we present a branch-and-price-and-cut algorithm to solve it exactly. To deal with two possible ways of serving requests, we first decompose the corresponding pricing problem into a shortest path problem and a knapsack problem, and then tackle them in the same bi-directional labeling algorithm framework. We also discuss acceleration techniques and implementation details to speed up the performance of the overall procedure. Computational experiments are conducted on a set of classic request instances, together with a set of randomly generated bid instances. With a time limit of two hours, numerical results validate the efficiency and effectiveness of the proposed algorithm. Finally, sensitivity analysis and managerial findings are also provided on the PDPCBT.en_US
dcterms.accessRightsembargoed accessen_US
dcterms.bibliographicCitationTransportation research. Part B, Methodological, Nov. 2023, v. 177, 102831en_US
dcterms.isPartOfTransportation research. Part B, Methodologicalen_US
dcterms.issued2023-11-
dc.identifier.scopus2-s2.0-85171626521-
dc.identifier.eissn1879-2367en_US
dc.identifier.artn102831en_US
dc.description.validate202406 bcchen_US
dc.description.oaNot applicableen_US
dc.identifier.FolderNumbera2776-
dc.identifier.SubFormID48307-
dc.description.fundingSourceRGCen_US
dc.description.pubStatusPublisheden_US
dc.date.embargo2025-11-30en_US
dc.description.oaCategoryGreen (AAM)en_US
Appears in Collections:Journal/Magazine Article
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Embargo End Date 2025-11-30
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