Coordinating aircraft maintenance routing and integrated maintenance staffing and rostering: a Stackelberg game theoretical model

Abstract

There is an interdependence between operational-based flight delay aircraft maintenance routing problem (AMRPD) and maintenance staffing problem (MSP). Furthermore, MSP and maintenance rostering problem (MRP) are interdependent. In the literature, most of the studies only consider a single interdependence and neglect the other one. This results in difficulties in implementing the optimal plan constructed by each problem, leading finally to an increase in the operational cost of airlines and maintenance providers. Therefore, the main objective of this study is to investigate these interdependences simultaneously. This is accomplished by developing a Stackelberg game model (LFSGM), in which leader and follower are the airlines and maintenance providers, respectively. This LFSGM is modelled as a bi-level mixed integer linear programming (MILP) model. The upper-level is represented by the AMRPD, while the integrated maintenance staffing and rostering (IMSR) functions as the lower-level. The solution of the LFSGM is obtained from an iterative algorithm. The viability and superiority of the LFSGM are demonstrated by presenting a case study of a leading airline in the Middle East serviced by four maintenance providers. The results reveal a significant cost saving for airline and maintenance providers.

KEYWORDS:

• Aircraft routing problem
• maintenance staffing problem
• maintenance rostering problem
• game theory
• maintenance scheduling

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The authors confirm that the data supporting the findings of this study are available within the article. Any other data will be available upon reasonable request.

Notes

1 https://www.iata.org/whatwedo/workgroups/Documents/ACC-2015-GVA/1630-1650-mtc-cost-trends.pdf

Additional information

Funding

The study presented in this article was mainly supported by a grant from the Research Committee of The Hong Kong Polytechnic University under project code P0036181 and RGC (Hong Kong), National Natural Science Foundation of China (grant number 71901052), and The Department of Education of Liaoning Province (grant number LJKZ1043).

Notes on contributors

Abdelrahman E. E. Eltoukhy

Abdelrahman E.E. Eltoukhy graduated with a B.Sc. degree in Production Engineering from Helwan University, Egypt, and received his M.Sc. degree in Engineering and Management from Politecnico Di Torino, Italy. He received his Ph.D. degree from The Hong Kong Polytechnic University, Hong Kong. Before joining The Hong Kong Polytechnic University, he worked as Assistant Professor in Systems Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia. Later, he moved to the Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, as a Research Assistant Professor. His current research interests include Airline Schedule Planning, Logistics and Supply Chain Management, Operations Research, Simulation, AI Optimization, and Robot Localization and Mapping.

Z. X. Wang

Z.X. Wang received the B.S. degree in Materials Science and Engineering from Dalian Jiaotong University, Dalian, China, in 2009, the M.S. degree in management science and engineering from the College of Transportation Engineering, Dalian Maritime University, Dalian, China, in 2011, and the Ph.D. degree from the Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong in 2016. He is currently a associate professor with the Department of Logistics Management, Dongbei University of Finance and Economics, Dalian, China. His current research interests include operation research, logistics management, supply chain management and aircraft scheduling.

I. A. Shaban

I.A. Shaban received his B.Sc. and M.Sc. degrees in Production Engineering from Helwan University, Egypt. Then, he received the Ph.D. degree from the Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong. He is currently a postdoctoral fellow in the Department of Building and Real Estate, The Hong Kong Polytechnic University, Hong Kong. His current research interests include operations, production and infrastructure management, revenue management, air cargo pricing, logistics and supply chain management. Dr. Ibrahim has published in top journals such as Computers & Industrial Engineering, Journal of Cleaner Production, and Expert Systems with Applications.

Felix T. S. Chan

Felix T.S. Chan received his BSc Degree in Mechanical Engineering from Brighton University, UK, and obtained his MSc and PhD in Manufacturing Engineering from the Imperial College of Science and Technology, University of London, UK. Prior joining Macau University of Science and Technology, Prof. Chan has many years of working experience in other universities, including The Hong Kong Polytechnic University; University of Hong Kong; University of South Australia; University of Strathclyde. His current research interests are Logistics and Supply Chain Management, Decision Making, AI Optimisation, Operations Research, Production and Operations Management, Distribution Coordination. Prof. Chan has published over 16 book chapters, over 390 SCI refereed international journal papers, and 320 peer reviewed international conference papers. His total number of citations > 11,000, h Index =  54. Prof. Chan is a chartered member of the Chartered Institute of Logistics and Transport in Hong Kong. Based on the recent compilations (2020) and (2021) from a research group of Stanford about the impact of scientists (top 2% listed). The work is published in the following websites: https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3000918; and doi: 10.17632/btchxktzyw.3. Prof. Felix Chan is categorised in the field of Operations Research, ranked 10 out of over 23,450 scientists worldwide, i.e. Top 0.04% worldwide, for TWO consecutive years (2020 and 2021).