Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/104384
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dc.contributorDepartment of Industrial and Systems Engineeringen_US
dc.creatorEltoukhy, AEEen_US
dc.creatorWang, ZXen_US
dc.creatorChan, FTSen_US
dc.creatorChung, SHen_US
dc.creatorMa, HLen_US
dc.creatorWang, XPen_US
dc.date.accessioned2024-02-05T08:49:20Z-
dc.date.available2024-02-05T08:49:20Z-
dc.identifier.issn2168-2216en_US
dc.identifier.urihttp://hdl.handle.net/10397/104384-
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.rights© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en_US
dc.rightsThe following publication Eltoukhy, A. E. E., Wang, Z. X., Chan, F. T. S., Chung, S. H., Ma, H.-L., & Wang, X. P. (2020). Robust Aircraft Maintenance Routing Problem Using a Turn-Around Time Reduction Approach. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 50(12), 4919–4932 is available at https://doi.org/10.1109/TSMC.2019.2937648.en_US
dc.subjectAircraft maintenance routing problem (AMRP)en_US
dc.subjectAirline operationsen_US
dc.subjectRobustnessen_US
dc.subjectTurn-around time (TRT)en_US
dc.titleRobust aircraft maintenance routing problem using a turn-around time reduction approachen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage4919en_US
dc.identifier.epage4932en_US
dc.identifier.volume50en_US
dc.identifier.issue12en_US
dc.identifier.doi10.1109/TSMC.2019.2937648en_US
dcterms.abstractThis article discusses the problem of how to efficiently build aircraft routes that better withstand potential disruptions, such as bad weather, technical problems, and passenger delays. This optimization problem is called robust aircraft maintenance routing problem (RAMRP). There are three approaches in the literature to deal with the RAMRP, such as the buffer time allocation approach (BT), the departure retiming approach (DR), and the scenario-based stochastic programming approach (SSP). Most of the previous approaches have some shortcomings in terms of fleet productivity and delay absorption. In addition, the majority of the RAMRP models overlook maintenance regulations, which result in the generation of infeasible routes. In this article, RAMRP is investigated with two main objectives. First, a novel robustness approach, called the turn-around time reduction approach (TRTR), that avoids the shortcomings of the existing approaches, is incorporated into RAMRP. The second objective is to develop an RAMRP model that simultaneously considers all maintenance regulations. The effectiveness of the proposed RAMRP model along with the TRTR is demonstrated using real data from a major Middle Eastern airline. The results reveal an improved performance of the TRTR over the BT by about 3.43%-12.20% and 2.5%-13.58%, while handling the expected propagated delay costs and fleet productivity, respectively. In addition, the results show that the TRTR is better than the SSP by about 2.07%-18.82%, while minimizing the propagated delay costs. Therefore, the TRTR has a great potential to be implemented in the actual industry.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationIEEE transactions on systems, man, and cybernetics. Systems, Dec, 2020, v. 50, no. 12, p. 4919-4932en_US
dcterms.isPartOfIEEE transactions on systems, man, and cybernetics. Systemsen_US
dcterms.issued2020-12-
dc.identifier.scopus2-s2.0-85096649259-
dc.identifier.eissn2168-2232en_US
dc.description.validate202402 bcchen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberISE-0226-
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextThe Natural Science Foundation of China; The Research Committee of Hong Kong Polytechnic Universityen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS42947006-
dc.description.oaCategoryGreen (AAM)en_US
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