Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/73837
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dc.contributorDepartment of Industrial and Systems Engineering-
dc.creatorNg, KKHen_US
dc.creatorLee, CKMen_US
dc.creatorChan, FTSen_US
dc.creatorQin, Yen_US
dc.date.accessioned2018-03-29T07:15:27Z-
dc.date.available2018-03-29T07:15:27Z-
dc.identifier.issn1366-5545en_US
dc.identifier.urihttp://hdl.handle.net/10397/73837-
dc.language.isoenen_US
dc.publisherPergamon Pressen_US
dc.rights© 2017 Elsevier Ltd. All rights reserved.en_US
dc.rights© 2017. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/.en_US
dc.subjectArtificial bee colony algorithmen_US
dc.subjectMin-max regret approachen_US
dc.subjectMixed-mode parallel runwaysen_US
dc.subjectRobust schedulingen_US
dc.subjectSwarm intelligenceen_US
dc.titleRobust aircraft sequencing and scheduling problem with arrival/departure delay using the min-max regret approachen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage115en_US
dc.identifier.epage136en_US
dc.identifier.volume106en_US
dc.identifier.doi10.1016/j.tre.2017.08.006en_US
dcterms.abstractThis study considers the aircraft sequencing and scheduling problem under the uncertainty of arrival and departure delays for multiple heterogeneous mixed-mode parallel runways. To enhance runway resilience, runway operations should remain robust to mitigate the effects of delay propagation. The main objective of this research was to identify an optimal schedule by evaluating the robustness of feasible solutions under its respective worst-case scenario. A novel artificial bee colony algorithm was developed and verified by experimental results. The proposed efficient artificial bee colony algorithm can obtain close-to-optimal results with less computational effort in regard to a one-hour flight traffic planning horizon.-
dcterms.accessRightsopen access-
dcterms.bibliographicCitationTransportation research. Part E, Logistics and transportation review, Oct. 2017, v. 106, p. 115-136en_US
dcterms.isPartOfTransportation research. Part E, Logistics and transportation reviewen_US
dcterms.issued2017-10-
dc.identifier.scopus2-s2.0-85028000344-
dc.identifier.eissn1878-5794en_US
dc.identifier.rosgroupid2017000703-
dc.description.ros2017-2018 > Academic research: refereed > Publication in refereed journal-
dc.description.validate201802 bcrc-
dc.description.oaAccepted Manuscript-
dc.identifier.FolderNumbera0768-n04-
dc.identifier.SubFormID1565-
dc.description.fundingSourceSelf-funded-
dc.description.pubStatusPublished-
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