Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/93928
DC FieldValueLanguage
dc.contributorDepartment of Logistics and Maritime Studiesen_US
dc.creatorYang, Xen_US
dc.creatorLiu, Zen_US
dc.creatorLi, Fen_US
dc.creatorXu, Zen_US
dc.date.accessioned2022-08-03T08:48:48Z-
dc.date.available2022-08-03T08:48:48Z-
dc.identifier.issn0305-0548en_US
dc.identifier.urihttp://hdl.handle.net/10397/93928-
dc.language.isoenen_US
dc.publisherPergamon Pressen_US
dc.subjectColumn generationen_US
dc.subjectDynamic programmingen_US
dc.subjectNP-hardnessen_US
dc.subjectProduction and transportationen_US
dc.subjectSchedulingen_US
dc.titleIntegrated production and transportation scheduling with order-dependent inventory holding costsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume136en_US
dc.identifier.doi10.1016/j.cor.2021.105477en_US
dcterms.abstractIn this study, we consider an integrated production and transportation scheduling problem faced by make-to-order manufacturers that adopt a commit-to-delivery business mode and cooperate with third-party logistics providers to deliver processed products to customers. The third-party logistics providers typically offer multiple shipping modes chosen by the manufacturers to deliver products, each shipping mode with a shipping time guarantee and a shipping cost function that is non-increasing in shipping time and sub-additive, non-decreasing in shipping quantity. The problem involves inventory holding costs which not only depend on the time that the products spend in temporary storage but also depend on customer types. The problem is to determine an integrated production and shipping schedule that satisfies the committed delivery due date limitations for the customers, such that the total cost of shipping and inventory holding is minimized. We investigate two cases with and without split delivery. For both cases, we first show that both of them are ordinarily NP-hard, prove that there exist no polynomial-time approximation algorithms with constant worst-case ratios, propose exact algorithms to solve them, and finally design column generation-based heuristic algorithms to find feasible solutions. The computational results demonstrate that the heuristic algorithms are capable of generating near-optimal solutions efficiently. We also consider two interesting practical variants of the problem.en_US
dcterms.accessRightsembargoed accessen_US
dcterms.bibliographicCitationComputers and operations research, Dec. 2021, v. 136, 105477en_US
dcterms.isPartOfComputers and operations researchen_US
dcterms.issued2021-12-
dc.identifier.scopus2-s2.0-85111218560-
dc.identifier.eissn1873-765Xen_US
dc.identifier.artn105477en_US
dc.description.validate202208 bckwen_US
dc.description.oaNot applicableen_US
dc.identifier.FolderNumberLMS-0009-
dc.description.fundingSourceSelf-fundeden_US
dc.description.pubStatusPublisheden_US
dc.date.embargo2024-12-31en_US
dc.identifier.OPUS54385869-
Appears in Collections:Journal/Magazine Article
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Embargo End Date 2024-12-31
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