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|Title:||Optimizing aircraft routing of airline and maintenance staffing of maintenance providers using game theoretic model||Authors:||Elsayed Elsayed Eltoukhy, Abdelrahman||Advisors:||Chan, T. S. Felix (ISE)||Keywords:||Airlines -- Management
Aircraft industry -- Management
Airplanes -- Maintenance and repair
|Issue Date:||2018||Publisher:||The Hong Kong Polytechnic University||Abstract:||Recently, aviation and airline maintenance providers are of the most significant worldwide industries. This is shown by the enormous growth in the number of passengers, which was around 3.5 billion passengers in 2015, expecting an annual growth of 5%. To cope with this passenger growth, the number of aircraft is expected to increase from 24,579 in 2014 to 29,955 in 2022. As a result, the aircraft maintenance cost paid by airlines to maintenance providers is expected to increase from US $62.1 billion in 2014 to US $90 billion in 2024. Despite this pleasing economic situation for airlines and maintenance providers, many difficult challenges have been emerged during the planning and operating processes. One of the challenges facing airlines is how to build efficient routes for their aircraft, while respecting the operational maintenance restrictions. In this regard, aircraft maintenance routing problem (AMRP) is very significant for airlines, as it builds the routes for their aircraft and schedule their maintenance visits. On the other hand, for the maintenance providers, it is a great challenge to manage the workforce capacity required to serve the increased number of aircraft. Therefore, maintenance staffing problem (MSP) is recognized as an effective tool for maintenance providers, as it manages the workforce capacity required to serve the airlines' aircraft.
In the existing research, on the focus of AMRP, most AMRP models consider one operational maintenance restriction, which is a single maintenance visit every four days and overlook the restrictions of the total cumulative flying time, the total number of take-offs, the workforce capacity and the working hours of the maintenance providers. Consequently, the generated routes are not applicable in real practice due to their infeasibility. This motivates us to develop a model, in which all the aforementioned restrictions are considered in a single model. Therefore, the routes determined by this model can be implemented in reality. In addition, an efficient solution algorithm is proposed for solving the developed model. Meanwhile, one of the glaring facts in the literature is that AMRP and MSP are studied independently, and their interdependence have not been investigated. To fulfil this research gap, a leader-follower Stackelberg game (LFSG) model is developed to capture this interdependence. Moreover, a nested ant colony optimization-based algorithm is proposed as a solution method for the game theoretic model. Towards the goal of showing the superiority of the proposed model, we present a case study of LFSG for one major airline and four maintenance providers located in the Middle East. The results show significant cost savings for all players. Although the LFSG presents a formulation for a unique problem in the literature, it overlooks one important aspect, called the price competition among the maintenance providers. Indeed, this aspect has a direct influence on the AMRP, as it changes the routing plan constructed by airlines. In this connection, it is imperative to consider the price competition among the maintenance providers besides the interdependence between AMRP and MSP. For this purpose, a Stackelberg-Nash game model (SNGM) is proposed to capture the above-mentioned problem. In addition, an iterative game algorithm is developed in order to obtain the overall Nash equilibrium for the SNGM. To demonstrate the viability of the proposed model, we use the previous case study, in which its results reveal significant savings for airline and maintenance providers. The contribution of this thesis is threefold. Firstly, proposing a new scalable AMRP that considers all the operational maintenance restrictions along with developing an efficient solution algorithm to solve this model. Secondly, developing a coordinated decision support system based on game theory to capture the interdependence between AMRP of airlines and MSP of maintenance providers. Lastly, modeling the previous interdependence in the presence of the price competition among the maintenance providers, we develop a new model, called Stackelberg-Nash game model.
|Description:||xix, 177 pages : color illustrations
PolyU Library Call No.: [THS] LG51 .H577P ISE 2018 Elsayed Elsayed Eltoukhy
|URI:||http://hdl.handle.net/10397/80219||Rights:||All rights reserved.|
|Appears in Collections:||Thesis|
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