Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/98260
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dc.contributorDepartment of Logistics and Maritime Studiesen_US
dc.creatorZhen, Len_US
dc.creatorSun, Qen_US
dc.creatorZhang, Wen_US
dc.creatorWang, Ken_US
dc.creatorYi, Wen_US
dc.date.accessioned2023-04-27T01:04:20Z-
dc.date.available2023-04-27T01:04:20Z-
dc.identifier.issn0160-5682en_US
dc.identifier.urihttp://hdl.handle.net/10397/98260-
dc.language.isoenen_US
dc.publisherPalgrave Macmillanen_US
dc.rights© Operational Research Society 2020en_US
dc.rightsThis is an Accepted Manuscript of an article published by Taylor & Francis in Journal of the Operational Research Society on 25 Sep 2020 (published online), available at: http://www.tandfonline.com/10.1080/01605682.2020.1776168.en_US
dc.subjectBerth allocationen_US
dc.subjectCarbon taxationen_US
dc.subjectColumn generationen_US
dc.subjectGreen porten_US
dc.subjectQuay crane assignmenten_US
dc.subjectUncertaintyen_US
dc.titleColumn generation for low carbon berth allocation under uncertaintyen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage2225en_US
dc.identifier.epage2240en_US
dc.identifier.volume72en_US
dc.identifier.issue10en_US
dc.identifier.doi10.1080/01605682.2020.1776168en_US
dcterms.abstractThis article investigates a low carbon-oriented berth allocation and quay crane assignment problem considering vessels’ uncertain arrival time and loading/unloading workload for vessels. A two-stage stochastic programming model is formulated based on a set of scenarios. The first stage designs a baseline schedule and the second stage adjusts the schedule in each scenario. A solution method is developed by using column generation techniques. Numerical experiments are conducted to validate the efficiency of our column generation-based solution method and the effectiveness of the proposed decision model. Some sensitivity analysis is also performed to draw some managerial implications.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationJournal of the Operational Research Society, 2021, v. 72, no. 10, p. 2225-2240en_US
dcterms.isPartOfJournal of the Operational Research Societyen_US
dcterms.issued2021-
dc.identifier.scopus2-s2.0-85091609947-
dc.identifier.eissn1476-9360en_US
dc.description.validate202304 bckwen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberLMS-0150-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextNational Natural Science Foundation of China; National Key R&D Program of Chinaen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS55189488-
dc.description.oaCategoryGreen (AAM)en_US
Appears in Collections:Journal/Magazine Article
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