Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/107702
DC FieldValueLanguage
dc.contributorDepartment of Logistics and Maritime Studiesen_US
dc.creatorZhen, Len_US
dc.creatorFan, Ten_US
dc.creatorLi, Hen_US
dc.creatorWang, Sen_US
dc.creatorTan, Zen_US
dc.date.accessioned2024-07-09T07:09:55Z-
dc.date.available2024-07-09T07:09:55Z-
dc.identifier.issn1366-5545en_US
dc.identifier.urihttp://hdl.handle.net/10397/107702-
dc.language.isoenen_US
dc.publisherPergamon Pressen_US
dc.subjectFreight flow allocationen_US
dc.subjectHigh-speed rail express deliveryen_US
dc.subjectMeta-heuristic solution approachen_US
dc.subjectTransportation resources arrangementen_US
dc.subjectTwo-stage stochastic programming modelen_US
dc.titleAn optimization model for express delivery with high-speed railwayen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume176en_US
dc.identifier.doi10.1016/j.tre.2023.103206en_US
dcterms.abstractWith the expansion of the high-speed railway (HSR) network in China, high-speed rail express delivery (HSReD) is being used to satisfy the increasing demand for express cargo. The decisions on transportation resources arrangement and freight flow allocation are two of the key issues for practical implementation of HSReD. In this study, we examine the above key issues by developing a two-stage stochastic integer linear programming model to maximize the expected net operation profit of HSReD. A meta-heuristic solution approach introduced some tailored tactics is proposed to speed up the process of solving the above model in the large-scale instances. Numerical experiments based on different sizes and practical investigation on China Railway Nanchang Group are conducted to validate the effectiveness of the proposed model and solution approach. Some managerial implications are also obtained based on the sensitivity analysis, which may be potentially useful for optimizing the daily operation management of HSReD.en_US
dcterms.accessRightsembargoed accessen_US
dcterms.bibliographicCitationTransportation research. Part E, Logistics and transportation review, Aug. 2023, v. 176, 103206en_US
dcterms.isPartOfTransportation research. Part E, Logistics and transportation reviewen_US
dcterms.issued2023-08-
dc.identifier.scopus2-s2.0-85162249826-
dc.identifier.eissn1878-5794en_US
dc.identifier.artn103206en_US
dc.description.validate202407 bcwhen_US
dc.description.oaNot applicableen_US
dc.identifier.FolderNumbera2982-
dc.identifier.SubFormID49023-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextNational Natural Science Foundation of Chinaen_US
dc.description.pubStatusPublisheden_US
dc.date.embargo2026-08-31en_US
dc.description.oaCategoryGreen (AAM)en_US
Appears in Collections:Journal/Magazine Article
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Embargo End Date 2026-08-31
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