Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/111378
DC FieldValueLanguage
dc.contributorDepartment of Logistics and Maritime Studiesen_US
dc.creatorLee, Een_US
dc.creatorCen, Xen_US
dc.creatorLo, HKen_US
dc.date.accessioned2025-02-25T03:22:30Z-
dc.date.available2025-02-25T03:22:30Z-
dc.identifier.issn1366-5545en_US
dc.identifier.urihttp://hdl.handle.net/10397/111378-
dc.language.isoenen_US
dc.publisherElsevier Ltden_US
dc.subjectDemand responsive transiten_US
dc.subjectFlexible busen_US
dc.subjectReliabilityen_US
dc.subjectStochastic dynamic demanden_US
dc.titleScheduling zonal-based flexible bus service under dynamic stochastic demand and time-dependent travel timeen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume168en_US
dc.identifier.doi10.1016/j.tre.2022.102931en_US
dcterms.abstractThis paper schedules the zonal-based flexible bus service (ZBFBS) considering elastic stochastic demand, stochastic location, time-dependent travel time, and passenger time window constraints based on a scheduled-based formulation. Unlike a traditional time–space network that stipulates the precise arrival and departure times on specific nodes, a zonal-based time–space network is proposed to define the routes in terms of zonal visits of the flexible buses while allowing for flexibility in their arrival and departure times to cater for randomness. The ZBFBS scheduling problem is formulated as a two-stage decision-dependent stochastic problem with recourse. The first stage schedules the zonal visits of flexible buses and the second stage matches each passenger with either flexible bus or ad hoc service, with the latter incurring extra cost to carry the unmatched passengers. To effectively solve the problem, a state-augmented network, that integrates time and zone, is proposed to reduce the number of variables. Moreover, relaxation formulations based on vehicle types and routes are introduced, with an insertion heuristic implemented for vehicle scheduling. The problem is solved by a gradient-based solution approach. Numerical studies demonstrate the efficiency and quality of the solution methods under a variety of ride requests, as well as its advantage over the frequency-based approach in substantially reducing the ad hoc service cost. The applicability of the model is validated by solving an instance of Chengdu, China, with real data.en_US
dcterms.accessRightsembargoed accessen_US
dcterms.bibliographicCitationTransportation research. Part E, Logistics and transportation review, Dec. 2022, v. 168, 102931en_US
dcterms.isPartOfTransportation research. Part E, Logistics and transportation reviewen_US
dcterms.issued2022-12-
dc.identifier.scopus2-s2.0-85141245714-
dc.identifier.eissn1878-5794en_US
dc.identifier.artn102931en_US
dc.description.validate202502 bcchen_US
dc.description.oaNot applicableen_US
dc.identifier.FolderNumbera3414 [Non PolyU]-
dc.identifier.SubFormID50074-
dc.description.fundingSourceRGCen_US
dc.description.pubStatusPublisheden_US
dc.date.embargo2025-12-31en_US
dc.description.oaCategoryGreen (AAM)en_US
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