Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/98309
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dc.contributorDepartment of Logistics and Maritime Studiesen_US
dc.creatorWang, Ken_US
dc.creatorZhen, Len_US
dc.creatorWang, Sen_US
dc.creatorLaporte, Gen_US
dc.date.accessioned2023-04-27T01:04:41Z-
dc.date.available2023-04-27T01:04:41Z-
dc.identifier.issn0041-1655en_US
dc.identifier.urihttp://hdl.handle.net/10397/98309-
dc.language.isoenen_US
dc.publisherInstitute for Operations Research and the Management Sciencesen_US
dc.rights© 2018 INFORMSen_US
dc.rightsThis is the accepted manuscript of the following article: Wang, K., Zhen, L., Wang, S., & Laporte, G. (2018). Column generation for the integrated berth allocation, quay crane assignment, and yard assignment problem. Transportation Science, 52(4), 812-834, which has been published in final form at https://doi.org/10.1287/trsc.2018.0822.en_US
dc.subjectBerth allocationen_US
dc.subjectColumn generationen_US
dc.subjectQuay crane assignmenten_US
dc.subjectYard managementen_US
dc.titleColumn generation for the integrated berth allocation, quay crane assignment, and yard assignment problemen_US
dc.typeJournal/Magazine Articleen_US
dc.description.otherinformationTitle on author’s file: Column generation for integrated berth allocation, quay crane assignment and yard assignment problemen_US
dc.identifier.spage812en_US
dc.identifier.epage834en_US
dc.identifier.volume52en_US
dc.identifier.issue4en_US
dc.identifier.doi10.1287/trsc.2018.0822en_US
dcterms.abstractThis study investigates an integrated optimization problem on the three main types of resources used in container terminals: berths, quay cranes, and yard storage space. It presents a mixed integer linear programming model, which takes account of the decisions of berth allocation, quay crane assignment, and yard storage space unit assignment for incoming vessels. In addition, since the majority of the liner shipping services operate according to a weekly arrival pattern, the periodicity of the plan is also considered in the model and in the proposed algorithm. To solve the model on large-scale instances, a column generation (CG) procedure is developed to provide a lower bound for the integrated problem, in which an exact pseudopolynomial algorithm is designed for the pricing problems. Using this procedure, we propose a CG-based heuristic with different solution strategies and apply dual stabilization techniques to accelerate the algorithm. Based on some realistic instances,we conduct extensive numerical experiments to validate the effectiveness of the proposed model and the efficiency of the algorithm. The results show that the CG-based heuristic can yield a good solution with an approximate 1% optimality gap within a much shorter computation time than that of CPLEX.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationTransportation science, July-Aug. 2018, v. 52, no. 4, p. 812-834en_US
dcterms.isPartOfTransportation scienceen_US
dcterms.issued2018-07-
dc.identifier.scopus2-s2.0-85052148352-
dc.description.validate202304 bckwen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberLMS-0295-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextNational Natural Science Foundation of China; Canadian Natural Sciences and Engineering Research Councilen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS24587127-
dc.description.oaCategoryGreen (AAM)en_US
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