Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/89918
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dc.contributorDepartment of Logistics and Maritime Studiesen_US
dc.creatorLee, CYen_US
dc.creatorShu, Sen_US
dc.creatorXu, Zen_US
dc.date.accessioned2021-05-13T08:32:41Z-
dc.date.available2021-05-13T08:32:41Z-
dc.identifier.issn1059-1478en_US
dc.identifier.urihttp://hdl.handle.net/10397/89918-
dc.language.isoenen_US
dc.publisherWiley-Blackwellen_US
dc.rights© 2020 Production and Operations Management Societyen_US
dc.rightsThis is the peer reviewed version of the following article: Lee, C.-Y., Shu, S. and Xu, Z. (2021), Optimal Global Liner Service Procurement by Utilizing Liner Service Schedules. Prod Oper Manag, 30: 703-714, which has been published in final form at https://doi.org/10.1111/poms.13311. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibited.en_US
dc.subject(mixed) integer linear programmingen_US
dc.subjectDemand uncertaintyen_US
dc.subjectLiner service procurementen_US
dc.subjectRobust optimizationen_US
dc.subjectService schedulesen_US
dc.titleOptimal global liner service procurement by utilizing liner service schedulesen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage703en_US
dc.identifier.epage714en_US
dc.identifier.volume30en_US
dc.identifier.issue3en_US
dc.identifier.doi10.1111/poms.13311en_US
dcterms.abstractFor global shippers (i.e., multinational manufacturers or retailers), strategic sourcing of container liner shipping services from ocean carriers is an important element of successful global supply chain management. We study how to utilize information about different ocean carriers’ liner service schedules so that shippers can optimize their sourcing decisions over the selection of carriers to transport container cargoes around the world through multiple shipping lanes. We first introduce a deterministic optimization problem, where cargo demands are given in advance and in which inventory holding costs are included to capture the impacts of liner service schedules on the total operating cost. We formulate the deterministic optimization problem as a mixed integer linear program, which can be simplified by exploiting a totally unimodular property, and can thus be solved directly by a general optimization solver. To further capture the impact of liner service schedules on shippers’ resilience to the uncertainties in cargo demands, we then introduce a two-stage robust optimization counterpart of the deterministic problem based on a probability-free demand uncertainty set. As the two-stage robust optimization problem is challenging to solve, we derive some novel reformulations that can enable us to develop an effective solution method. By exploiting the information about liner service schedules, we show how our proposed models and solution method can help shippers to optimize their liner service procurement decisions.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationProduction and operations management, Mar. 2021, v. 30, no.3, p. 703-714en_US
dcterms.isPartOfProduction and operations managementen_US
dcterms.issued2021-03-
dc.identifier.scopus2-s2.0-85097386194-
dc.identifier.eissn1937-5956en_US
dc.description.validate202105 bcvcen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumbera0831-n03-
dc.identifier.SubFormID1936-
dc.description.fundingSourceRGCen_US
dc.description.fundingText152240/17Een_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryGreen (AAM)en_US
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