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dc.contributor.authorGan, Mi
dc.contributor.authorLi, Dandan
dc.contributor.authorYao, Zhu
dc.contributor.authorYu, Hao
dc.contributor.authorOu, Qichen
dc.date.accessioned2024-07-05T07:49:07Z
dc.date.available2024-07-05T07:49:07Z
dc.date.issued2024-06-27
dc.description.abstractRailway cold chain service network design (RCC-SND) aims to optimize the utilization of stations and lines as well as train allocations in a manner that minimizes costs while satisfying the service requirements of shippers. Furthermore, the uncertainties associated with freight demand, transportation costs, quality loss, station handling capacity, and arc capacity make the RCC-SND a complex decision-making problem. To tackle this challenge, we first formulate a Mixed-Integer Nonlinear Programming (MINLP) model to determine hub locations, freight wagon flows, and service frequency. To cope with uncertain parameters with varying degrees of uncertainty incorporated in the model, we extend the problem using fuzzy programming and further convert it to its crisp counterpart. A real-world cases study in Southwest China is performed to validate the proposed model, whose results provide different strategies for decision-makers with varying preferences. There are some main findings: As the number of hubs increases from 5 to 6, a maximum total cost savings of 1.99% can be achieved. Railway operators may opt for different decision preferences, for decisions prioritizing economic efficiency, the cost can decrease by 2.69% compared to deterministic optimization.en_US
dc.identifier.citationGan, Li, Yao, Yu, Ou. Intelligent decision modeling for optimizing railway cold chain service networks under uncertainty. Information Sciences. 2024;679en_US
dc.identifier.cristinIDFRIDAID 2279778
dc.identifier.doi10.1016/j.ins.2024.121112
dc.identifier.issn0020-0255
dc.identifier.issn1872-6291
dc.identifier.urihttps://hdl.handle.net/10037/34080
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.relation.journalInformation Sciences
dc.relation.projectIDHK-dir - Direktoratet for høyere utdanning og kompetanse: UTF-2021/10166en_US
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2024 The Author(s)en_US
dc.titleIntelligent decision modeling for optimizing railway cold chain service networks under uncertaintyen_US
dc.type.versionacceptedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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