An approximate dynamic programming approach for solving aircraft fleet engine maintenance problem: Methodology and a case study

作     者：Zhang, Miao Yang, Jingyuan Zhang, Chuwen He, Simai Liu, Huikang Wang, Jinshen Wang, Zizhuo 

作者机构：Shanghai Univ Finance & Econ Sch Informat Management & Engn Shanghai 200433 Peoples R China Univ Chicago Booth Sch Business Chicago IL 60637 USA Shanghai Jiao Tong Univ Antai Coll Econ & Management Shanghai 200240 Peoples R China China Southern Airlines Co Ltd Guangzhou 510403 Peoples R China Chinese Univ Hong Kong Sch Data Sci Shenzhen 518172 Guangdong Peoples R China Cardinal Operat Co Ltd Beijing 100102 Peoples R China 

出 版 物：《EUROPEAN JOURNAL OF OPERATIONAL RESEARCH》 (Eur J Oper Res)

年 卷 期：2025年第321卷第3期

页      面：958-973页

核心收录：

学科分类：1201[管理学-管理科学与工程(可授管理学、工学学位)] 07[理学] 070104[理学-应用数学] 0701[理学-数学] 

基　　金：National Natural Science Foundation of China (NSFC) [NSFC-72150001, 72225009, 72394360, 72394365, NSFC-72192830, 72192832, 71825003, NSFC-72394361, 72425013] Guangdong Key Lab of Mathematical Foundations for Artificial Intelligence 

主　　题：OR in airlines Engine maintenance Fleet management Multi-stage stochastic integer programming Approximate dynamic programming 

摘      要：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.