{"title":"大型飞机长期维修调度与工位分配优化模型","authors":"JohnPaul Adimonyemma, Yanshuo Sun","doi":"10.1016/j.tre.2025.104302","DOIUrl":null,"url":null,"abstract":"<div><div>The primary focus of the existing aircraft maintenance optimization literature is on short-term aircraft maintenance routing. By contrast, only a few studies address long-term maintenance planning, which predominantly emphasize scheduling decisions: none of them have examined the critical aspect of assigning aircraft to maintenance stations, a key challenge for major airlines with a network of maintenance facilities. Additional research gaps include (1) insufficient consideration of practical maintenance-related constraints (e.g., station access limit and aircraft rotation requirement) and (2) the absence of scalable algorithms capable of solving real-world problem instances involving hundreds of aircraft and dozens of maintenance stations. To fill those gaps, this study introduces a joint optimization model for aircraft maintenance scheduling and station assignment to assist a U.S.-based airline in creating long-term plans for a fleet of over 800 aircraft of multiple subfleet types. To address the computational challenges, we propose two decomposition approaches: one based on decision types and the other on time horizons. Extensive computational experiments using real-world data from the collaborating airline demonstrate that these approaches can reduce computation time by up to 80% with a minimal increase in the optimization objective (less than 2%). The proposed model is expected to streamline maintenance planning efforts and enhance outcomes for aircraft maintenance professionals.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"202 ","pages":"Article 104302"},"PeriodicalIF":8.3000,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimization model for large-scale long-term aircraft maintenance scheduling and station assignment\",\"authors\":\"JohnPaul Adimonyemma, Yanshuo Sun\",\"doi\":\"10.1016/j.tre.2025.104302\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The primary focus of the existing aircraft maintenance optimization literature is on short-term aircraft maintenance routing. By contrast, only a few studies address long-term maintenance planning, which predominantly emphasize scheduling decisions: none of them have examined the critical aspect of assigning aircraft to maintenance stations, a key challenge for major airlines with a network of maintenance facilities. Additional research gaps include (1) insufficient consideration of practical maintenance-related constraints (e.g., station access limit and aircraft rotation requirement) and (2) the absence of scalable algorithms capable of solving real-world problem instances involving hundreds of aircraft and dozens of maintenance stations. To fill those gaps, this study introduces a joint optimization model for aircraft maintenance scheduling and station assignment to assist a U.S.-based airline in creating long-term plans for a fleet of over 800 aircraft of multiple subfleet types. To address the computational challenges, we propose two decomposition approaches: one based on decision types and the other on time horizons. Extensive computational experiments using real-world data from the collaborating airline demonstrate that these approaches can reduce computation time by up to 80% with a minimal increase in the optimization objective (less than 2%). The proposed model is expected to streamline maintenance planning efforts and enhance outcomes for aircraft maintenance professionals.</div></div>\",\"PeriodicalId\":49418,\"journal\":{\"name\":\"Transportation Research Part E-Logistics and Transportation Review\",\"volume\":\"202 \",\"pages\":\"Article 104302\"},\"PeriodicalIF\":8.3000,\"publicationDate\":\"2025-07-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transportation Research Part E-Logistics and Transportation Review\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1366554525003436\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Research Part E-Logistics and Transportation Review","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1366554525003436","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
Optimization model for large-scale long-term aircraft maintenance scheduling and station assignment
The primary focus of the existing aircraft maintenance optimization literature is on short-term aircraft maintenance routing. By contrast, only a few studies address long-term maintenance planning, which predominantly emphasize scheduling decisions: none of them have examined the critical aspect of assigning aircraft to maintenance stations, a key challenge for major airlines with a network of maintenance facilities. Additional research gaps include (1) insufficient consideration of practical maintenance-related constraints (e.g., station access limit and aircraft rotation requirement) and (2) the absence of scalable algorithms capable of solving real-world problem instances involving hundreds of aircraft and dozens of maintenance stations. To fill those gaps, this study introduces a joint optimization model for aircraft maintenance scheduling and station assignment to assist a U.S.-based airline in creating long-term plans for a fleet of over 800 aircraft of multiple subfleet types. To address the computational challenges, we propose two decomposition approaches: one based on decision types and the other on time horizons. Extensive computational experiments using real-world data from the collaborating airline demonstrate that these approaches can reduce computation time by up to 80% with a minimal increase in the optimization objective (less than 2%). The proposed model is expected to streamline maintenance planning efforts and enhance outcomes for aircraft maintenance professionals.
期刊介绍:
Transportation Research Part E: Logistics and Transportation Review is a reputable journal that publishes high-quality articles covering a wide range of topics in the field of logistics and transportation research. The journal welcomes submissions on various subjects, including transport economics, transport infrastructure and investment appraisal, evaluation of public policies related to transportation, empirical and analytical studies of logistics management practices and performance, logistics and operations models, and logistics and supply chain management.
Part E aims to provide informative and well-researched articles that contribute to the understanding and advancement of the field. The content of the journal is complementary to other prestigious journals in transportation research, such as Transportation Research Part A: Policy and Practice, Part B: Methodological, Part C: Emerging Technologies, Part D: Transport and Environment, and Part F: Traffic Psychology and Behaviour. Together, these journals form a comprehensive and cohesive reference for current research in transportation science.