An approximate dynamic programming approach for solving aircraft fleet engine maintenance problem: Methodology and a case study
We consider a long-term engine maintenance planning problem for an aircraft fleet. The objective is to guarantee sufficient on-wing engines to reach service levels while effectively organizing shop visits for engines. However, complexity arises from intricate maintenance policies and uncertainty in...
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| Veröffentlicht in: | European journal of operational research Jg. 321; H. 3; S. 958 - 973 |
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| Sprache: | Englisch |
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16.03.2025
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| ISSN: | 0377-2217 |
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| Abstract | We consider a long-term engine maintenance planning problem for an aircraft fleet. The objective is to guarantee sufficient on-wing engines to reach service levels while effectively organizing shop visits for engines. However, complexity arises from intricate maintenance policies and uncertainty in engine deterioration. To address this problem, we propose a graph-based approach representing high-dimensional engine statuses and transitions. We then formulate the problem as a multi-stage stochastic integer program with endogenous uncertainty. We develop an approximate dynamic programming algorithm enhanced by dynamic graph generation and policy-sifting techniques so as to reduce the computational overhead in large problems. We demonstrate the efficacy of our method, compared with other popular methods, in terms of running time and solution quality. In the case study, we present an implementation in a real-world decision system in China Southern Airlines, in which the proposed method works seamlessly with other supporting modules and significantly improves the efficiency of engine maintenance management.
•We study an aircraft fleet engine maintenance management problem.•We develop a graph-based approach to capture dynamics between engine statuses.•We propose an approximate dynamic programming algorithm to solve this problem.•We demonstrate the effectiveness of our proposed method via numerical experiments.•We implement our methods with China Southern Airlines with success. |
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| AbstractList | We consider a long-term engine maintenance planning problem for an aircraft fleet. The objective is to guarantee sufficient on-wing engines to reach service levels while effectively organizing shop visits for engines. However, complexity arises from intricate maintenance policies and uncertainty in engine deterioration. To address this problem, we propose a graph-based approach representing high-dimensional engine statuses and transitions. We then formulate the problem as a multi-stage stochastic integer program with endogenous uncertainty. We develop an approximate dynamic programming algorithm enhanced by dynamic graph generation and policy-sifting techniques so as to reduce the computational overhead in large problems. We demonstrate the efficacy of our method, compared with other popular methods, in terms of running time and solution quality. In the case study, we present an implementation in a real-world decision system in China Southern Airlines, in which the proposed method works seamlessly with other supporting modules and significantly improves the efficiency of engine maintenance management.
•We study an aircraft fleet engine maintenance management problem.•We develop a graph-based approach to capture dynamics between engine statuses.•We propose an approximate dynamic programming algorithm to solve this problem.•We demonstrate the effectiveness of our proposed method via numerical experiments.•We implement our methods with China Southern Airlines with success. |
| Author | Zhang, Miao Wang, Zizhuo Yang, Jingyuan He, Simai Wang, Jinshen Zhang, Chuwen Liu, Huikang |
| Author_xml | – sequence: 1 givenname: Miao orcidid: 0009-0009-7745-4856 surname: Zhang fullname: Zhang, Miao email: serena.zhangm@gmail.com organization: School of Information Management and Engineering, Shanghai University of Finance and Economics, Shanghai, 200433, China – sequence: 2 givenname: Jingyuan surname: Yang fullname: Yang, Jingyuan email: jyang21@chicagobooth.edu organization: Booth School of Business, University of Chicago, Chicago, 60637, IL, United States of America – sequence: 3 givenname: Chuwen surname: Zhang fullname: Zhang, Chuwen email: chuwzhang@gmail.com organization: School of Information Management and Engineering, Shanghai University of Finance and Economics, Shanghai, 200433, China – sequence: 4 givenname: Simai surname: He fullname: He, Simai email: simaihe@sjtu.edu.cn organization: Antai College of Economics and Management, Shanghai Jiao Tong University, Shanghai, 200240, China – sequence: 5 givenname: Huikang surname: Liu fullname: Liu, Huikang email: hkl1u@sjtu.edu.cn organization: Antai College of Economics and Management, Shanghai Jiao Tong University, Shanghai, 200240, China – sequence: 6 givenname: Jinshen surname: Wang fullname: Wang, Jinshen email: jason-wang@csair.com organization: China Southern Airlines Company Limited, Guangzhou, 510403, China – sequence: 7 givenname: Zizhuo orcidid: 0000-0003-0828-7280 surname: Wang fullname: Wang, Zizhuo email: wangzizhuo@cuhk.edu.cn organization: School of Data Science, The Chinese University of Hong Kong, Shenzhen, Guangdong, 518172, China |
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| Keywords | OR in airlines Approximate dynamic programming Fleet management Engine maintenance Multi-stage stochastic integer programming |
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| SubjectTerms | Approximate dynamic programming Engine maintenance Fleet management Multi-stage stochastic integer programming OR in airlines |
| Title | An approximate dynamic programming approach for solving aircraft fleet engine maintenance problem: Methodology and a case study |
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