Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/98370
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dc.contributorDepartment of Logistics and Maritime Studiesen_US
dc.creatorZhen, Len_US
dc.creatorYu, Sen_US
dc.creatorWang, Sen_US
dc.creatorSun, Zen_US
dc.date.accessioned2023-04-27T01:05:06Z-
dc.date.available2023-04-27T01:05:06Z-
dc.identifier.issn0254-5330en_US
dc.identifier.urihttp://hdl.handle.net/10397/98370-
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.rights© Springer Science+Business Media New York 2016en_US
dc.rightsThis version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use(https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms), but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/s10479-016-2335-9.en_US
dc.subjectContainer port operationen_US
dc.subjectOR in transportationen_US
dc.subjectQuay cranesen_US
dc.subjectSchedulingen_US
dc.subjectYard trucksen_US
dc.titleScheduling quay cranes and yard trucks for unloading operations in container portsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage455en_US
dc.identifier.epage478en_US
dc.identifier.volume273en_US
dc.identifier.issue1-2en_US
dc.identifier.doi10.1007/s10479-016-2335-9en_US
dcterms.abstractThis paper studies an integrated optimization problem on quay crane and yard truck scheduling in container terminals. A mixed-integer programming model is formulated. For the model, we show the integrated scheduling problem is strongly NP-hard and investigate some properties that can considerably reduce the computational complexity. For solving the proposed model within a reasonable time, a particle swarm optimization based solution method is developed. Numerical experiments are conducted to compare the proposed method with the CPLEX solver and the genetic algorithm. The results validate the effectiveness of the proposed model and the efficiency of the proposed solution method.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationAnnals of operations research, 15 Feb. 2019, v. 273, no. 1-2, p. 455-478en_US
dcterms.isPartOfAnnals of operations researchen_US
dcterms.issued2019-02-15-
dc.identifier.scopus2-s2.0-84990866179-
dc.identifier.eissn1572-9338en_US
dc.description.validate202304 bckwen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberLMS-0471-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextNational Natural Science Foundation of China; Shanghai Social Science Research Programen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS6685139-
dc.description.oaCategoryGreen (AAM)en_US
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