DC FieldValueLanguage
dc.contributorDepartment of Logistics and Maritime Studies-
dc.creatorHuang, Den_US
dc.creatorChen, Xen_US
dc.creatorLiu, Zen_US
dc.creatorLyu, Cen_US
dc.creatorWang, Sen_US
dc.creatorChen, Xen_US
dc.date.accessioned2021-05-13T08:31:53Z-
dc.date.available2021-05-13T08:31:53Z-
dc.identifier.issn1366-5545en_US
dc.identifier.urihttp://hdl.handle.net/10397/89868-
dc.language.isoenen_US
dc.publisherPergamon Pressen_US
dc.subjectBike repositioningen_US
dc.subjectDemand forecastingen_US
dc.subjectHub-and-spoke network frameworken_US
dc.subjectHub-first-route-seconden_US
dc.subjectRandom forestsen_US
dc.titleA static bike repositioning model in a hub-and-spoke network frameworken_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage1en_US
dc.identifier.epage21en_US
dc.identifier.volume141en_US
dc.identifier.doi10.1016/j.tre.2020.102031en_US
dcterms.abstractThis paper addresses a static bike repositioning problem by embedding a short-term demand forecasting process, the Random Forest (RF) model, to account for the demand dynamics in the daytime. To tackle the heterogeneous repositioning fleets, a novel repositioning operation strategy constructed on the hub-and-spoke network framework is proposed. The repositioning optimization model is formulated using mixed-integer programming. An artificial bee colony algorithm, integrated with a commercial solver, is applied to address computational complexity. Experimental results show that the RF can achieve a high forecasting accuracy, and the proposed repositioning strategy can efficiently decrease the users’ dissatisfaction.-
dcterms.accessRightsembargoed access-
dcterms.bibliographicCitationTransportation research. Part E, Logistics and transportation review, Sept. 2020, v. 141, 102031, p. 1-21, https://doi.org/10.1016/j.tre.2020.102031en_US
dcterms.isPartOfTransportation research. Part E, Logistics and transportation reviewen_US
dcterms.issued2020-09-
dc.identifier.scopus2-s2.0-85088984121-
dc.identifier.eissn1878-5794en_US
dc.identifier.artn102031en_US
dc.description.validate202105 bchy-
dc.description.oaNot applicable-
dc.identifier.FolderNumbera0794-n06-
dc.identifier.SubFormID1657-
dc.description.fundingSourceOthers-
dc.description.fundingTextNSFC projects-
dc.description.pubStatusEarly release-
dc.date.embargo2023.09.30en_US
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