Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/104556
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dc.contributorDepartment of Industrial and Systems Engineeringen_US
dc.creatorEltoukhy, AEEen_US
dc.creatorChan, FTSen_US
dc.creatorChung, SHen_US
dc.creatorQu, Ten_US
dc.date.accessioned2024-02-05T08:51:05Z-
dc.date.available2024-02-05T08:51:05Z-
dc.identifier.urihttp://hdl.handle.net/10397/104556-
dc.description47th International Conference on Computers & Industrial Engineering : How Digital Platforms and Industrial Engineering are Transforming Industry and Services, Universidade Nova de Lisboa, Lisbon, Portugal, 11th-13th October 2017en_US
dc.language.isoenen_US
dc.publisherFaculdade de Ciências e Tecnologia, Universidade Nova de Lisboaen_US
dc.rightsCopyright CIE47-47th International Conference on Computers & Industrial Engineeringen_US
dc.rightsPosted with permission of the publisher.en_US
dc.subjectAircraft routing problemen_US
dc.subjectMaintenance staffing problemen_US
dc.subjectStackelberg gameen_US
dc.titleStackelberg game theoretical model for optimizing aircraft maintenance routing with maintenance staffingen_US
dc.typeConference Paperen_US
dcterms.abstractDespite the interdependence between the operational aircraft maintenance routing problem with flight delay consideration (OAMRPFD) and the maintenance staffing problem (MSP), they are solved separately. Therefore, the optimal plan of each problem will not be operated as planned. In this paper, our focus is the OAMRPFD along with the MSP, with two main objectives. Firstly, to develop an OAMRPFD model that reflects appropriately the flight delays. For this purpose, a new scenario-based stochastic programming model for OAMRPFD (SOAMRPFD) is proposed. Secondly, to handle the interdependence between SOAMRPFD and MSP, by proposing a coordinated configuration of SOAMRPFD and MSP that is formulated as a leader-follower Stackelberg game. In this game, SOAMRPFD acts as a leader and MSP acts as a follower. This game is enacted through a bi-level optimization model, which is solved by a bi-level nested ant colony optimization (ACO) algorithm. In order to demonstrate the superiority of the proposed model, a case study of major airline and maintenance companies located in the Middle East is presented.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationProceedings of the 47th International Conference on Computers & Industrial Engineering (CIE47), Lisbon, Portugal, 11-13 October 2017,169en_US
dcterms.issued2017-
dc.relation.ispartofbookThe Proceedings of the 47th International Conference on Computers & Industrial Engineering (CIE47)en_US
dc.relation.conferenceInternational Conference on Computers & Industrial Engineering [CIE]en_US
dc.identifier.artn169en_US
dc.description.validate202402 bcchen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberISE-0880-
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.OPUS9610903-
dc.description.oaCategoryPublisher permissionen_US
Appears in Collections:Conference Paper
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