Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/104104
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Title: Data analytics in managing aircraft routing and maintenance staffing with price competition by a Stackelberg-Nash game model
Authors: Eltoukhy, AEE 
Wang, ZX
Chan, FTS 
Fu, X 
Issue Date: Feb-2019
Source: Transportation research. Part E, Logistics and transportation review, Feb. 2019, v. 122, p. 143-168
Abstract: This study develops a Stackelberg-Nash game model (SNGM) to capture the interdependence between aircraft routing of airlines and maintenance staffing of maintenance providers, and to consider the price competition among maintenance providers. The SNGM’s overall Nash equilibrium is obtained using an iterative game algorithm. The SNGM effectiveness is demonstrated with a case study, in which a neural network-based algorithm is developed to forecast accurate non-propagated delays, and a multiple linear regression algorithm is adopted to predict demand-price relationship for each maintenance provider. The results reveal cost savings of about 26% and 22% for the airline and the maintenance providers, respectively.
Keywords: Aircraft routing problem
Data analytics
Game theory
Maintenance staffing problem
Publisher: Elsevier Ltd
Journal: Transportation research. Part E, Logistics and transportation review 
ISSN: 1366-5545
EISSN: 1878-5794
DOI: 10.1016/j.tre.2018.12.002
Rights: © 2018 Elsevier Ltd. All rights reserved
© 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/
The following publication Eltoukhy, A. E. E., Wang, Z. X., Chan, F. T. S., & Fu, X. (2019). Data analytics in managing aircraft routing and maintenance staffing with price competition by a Stackelberg-Nash game model. Transportation Research Part E: Logistics and Transportation Review, 122, 143–168 is available at https://doi.org/10.1016/j.tre.2018.12.002.
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