Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/107721
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dc.contributorDepartment of Logistics and Maritime Studiesen_US
dc.creatorQi, Jen_US
dc.creatorChen, Ten_US
dc.creatorZheng, Jen_US
dc.creatorWang, Sen_US
dc.date.accessioned2024-07-09T07:10:02Z-
dc.date.available2024-07-09T07:10:02Z-
dc.identifier.urihttp://hdl.handle.net/10397/107721-
dc.language.isoenen_US
dc.publisherMDPI AGen_US
dc.rights© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).en_US
dc.rightsThe following publication Qi J, Chen T, Zheng J, Wang S. Port Call Optimization at a Ferry Terminal with Stochastic Servicing Time and Additional Visits. Journal of Marine Science and Engineering. 2023; 11(9):1644 is available at https://doi.org/10.3390/jmse11091644.en_US
dc.subjectFerry shippingen_US
dc.subjectPort call optimizationen_US
dc.subjectStochastic servicing timeen_US
dc.subjectVisit schedule engineeringen_US
dc.titlePort call optimization at a ferry terminal with stochastic servicing time and additional visitsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume11en_US
dc.identifier.issue9en_US
dc.identifier.doi10.3390/jmse11091644en_US
dcterms.abstractFerry shipping is an indispensable method of public transportation, especially in areas with well-developed river systems or coastal areas. The increasing demand for transport requires additional visits and introduces the problem of ship visit schedule engineering at ferry terminals with stochastic servicing time. In this paper, we propose a ferry visit planning problem to maximize the total profit, in which the berthing time, berthing location, and servicing time for each ferry visit are optimized. Then, a mixed-integer nonlinear programming model is proposed to formulate the focal problem. We propose a tailored solution method to convert the mixed-integer nonlinear programming model to a mixed-integer linear programming model. We further devise an inserting algorithm to test the performance of our model. A comparison between the results of the basic instance yielded by our model and those of the inserting algorithm validates our model and solution method. We then conduct sensitivity analyses of the impacts of different numbers of existing ferry visits and added ferry visits, different expectations of the real time taken by all the ferry visits, and different distribution patterns of existing ferry visits, to further validate the performance of our model.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationJournal of marine science and engineering, Sept. 2023, v. 11, no. 9, 1644en_US
dcterms.isPartOfJournal of marine science and engineeringen_US
dcterms.issued2023-09-
dc.identifier.scopus2-s2.0-85172781984-
dc.identifier.eissn2077-1312en_US
dc.identifier.artn1644en_US
dc.description.validate202407 bcwhen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumbera2984-
dc.identifier.SubFormID49044-
dc.description.fundingSourceSelf-fundeden_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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