Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/106815
DC FieldValueLanguage
dc.contributorFaculty of Business-
dc.creatorWang, W-
dc.creatorWang, S-
dc.creatorZhen, L-
dc.creatorLaporte, G-
dc.date.accessioned2024-06-04T07:39:56Z-
dc.date.available2024-06-04T07:39:56Z-
dc.identifier.issn0191-2615-
dc.identifier.urihttp://hdl.handle.net/10397/106815-
dc.language.isoenen_US
dc.publisherElsevier Ltden_US
dc.subjectAutonomous shipen_US
dc.subjectBenders decompositionen_US
dc.subjectBranch-and-cuten_US
dc.subjectSample average approximationen_US
dc.subjectShipping company operationsen_US
dc.titleThe impact of autonomous ships in regional waterwaysen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume178-
dc.identifier.doi10.1016/j.trb.2023.102851-
dcterms.abstractTechnological innovation has been reshaping all walks of life, and the marine shipping industry is no exception. Autonomous vessels have gained significant attention due to their numerous advantages. However, regulatory constraints and expensive manufacturing costs are impeding the application of autonomous vessels. To overcome these challenges, this research conducts experiments with autonomous ships on national waterways with less regulation and develops a model to investigate their impact on shipping company operations. The model simultaneously optimizes ship routing, fleet sizing, fleet deployment, and demand fulfillment, taking into account demand uncertainty. Two solution methods, i.e., sample average approximation and a two-phase Benders-based branch-and-cut algorithm, are proposed to solve the problem with acceleration strategies, including column generation and variable fixing. The performance of several solution techniques is tested through numerical experiments using real-world data. Besides, sensitivity analyses are conducted to further discuss the influence of key factors and derive constructive managerial insights for shipping companies.-
dcterms.accessRightsembargoed accessen_US
dcterms.bibliographicCitationTransportation research. Part B, Methodological, Dec. 2023, v. 178, 102851-
dcterms.isPartOfTransportation research. Part B, Methodological-
dcterms.issued2023-12-
dc.identifier.scopus2-s2.0-85175338708-
dc.identifier.eissn1879-2367-
dc.identifier.artn102851-
dc.description.validate202406 bcch-
dc.identifier.FolderNumbera2751en_US
dc.identifier.SubFormID48231en_US
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextNational Natural Science Foundation of Chinaen_US
dc.description.pubStatusPublisheden_US
dc.date.embargo2025-12-31en_US
dc.description.oaCategoryGreen (AAM)en_US
Appears in Collections:Journal/Magazine Article
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Embargo End Date 2025-12-31
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