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Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.tre.2017.07.006
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dc.titleA bi-objective robust model for berth allocation scheduling under uncertainty
dc.contributor.authorXiang, Xi
dc.contributor.authorLiu, Changchun
dc.contributor.authorMiao, Lixin
dc.date.accessioned2019-06-06T05:19:01Z
dc.date.available2019-06-06T05:19:01Z
dc.date.issued2017-10-01
dc.identifier.citationXiang, Xi, Liu, Changchun, Miao, Lixin (2017-10-01). A bi-objective robust model for berth allocation scheduling under uncertainty. TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 106 (C) : 294-319. ScholarBank@NUS Repository. https://doi.org/10.1016/j.tre.2017.07.006
dc.identifier.issn1366-5545
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/155206
dc.description.abstract© 2017 Elsevier Ltd This study examines the berth allocation problem with the consideration of uncertainty factors, including the arrival and operation times of the calling vessels. A bi-objective robust berth allocation model, which focuses on economic performance and customer satisfaction, is formulated. The model aims to optimize the robustness of the berth allocation policy, and an adaptive grey wolf optimizer algorithm is developed to solve the proposed model. The performance of the heuristic is evaluated through randomly generated instances. Experimental results show that the proposed heuristic provides good solution quality and calculation efficiency.
dc.language.isoen
dc.publisherPERGAMON-ELSEVIER SCIENCE LTD
dc.sourceElements
dc.subjectSocial Sciences
dc.subjectScience & Technology
dc.subjectTechnology
dc.subjectEconomics
dc.subjectEngineering, Civil
dc.subjectOperations Research & Management Science
dc.subjectTransportation
dc.subjectTransportation Science & Technology
dc.subjectBusiness & Economics
dc.subjectEngineering
dc.subjectContainer terminals
dc.subjectBerth allocation scheduling problem
dc.subjectRobust optimization
dc.subjectAdaptive grey wolf optimizer algorithm
dc.subjectUncertainty
dc.subjectGREY WOLF OPTIMIZER
dc.subjectCONTAINER TERMINALS
dc.subjectOPERATIONS-RESEARCH
dc.subjectHANDLING TIME
dc.subjectTABU SEARCH
dc.subjectPORT
dc.subjectFORMULATION
dc.subjectHEURISTICS
dc.subjectALGORITHM
dc.typeArticle
dc.date.updated2019-06-03T08:21:54Z
dc.contributor.departmentINST OF OPERATIONS RESEARCH & ANALYTICS
dc.description.doi10.1016/j.tre.2017.07.006
dc.description.sourcetitleTRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
dc.description.volume106
dc.description.issueC
dc.description.page294-319
dc.published.statePublished
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