{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,26]],"date-time":"2025-11-26T08:08:25Z","timestamp":1764144505094,"version":"3.46.0"},"reference-count":26,"publisher":"Springer Science and Business Media LLC","issue":"16","license":[{"start":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T00:00:00Z","timestamp":1761523200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T00:00:00Z","timestamp":1761523200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Research Fund of Nanjing University of Aeronautics and Astronautics","award":["1007-YAT23021"],"award-info":[{"award-number":["1007-YAT23021"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U2033205"],"award-info":[{"award-number":["U2033205"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Appl Intell"],"published-print":{"date-parts":[[2025,11]]},"DOI":"10.1007\/s10489-025-06844-0","type":"journal-article","created":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T08:19:04Z","timestamp":1761553144000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Robust optimization of aircraft maintenance routing based on the adaptive reinforcement learning algorithm"],"prefix":"10.1007","volume":"55","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8786-1879","authenticated-orcid":false,"given":"Haoyu","family":"Zhang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weiwei","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chengjin","family":"Ding","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiahui","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,10,27]]},"reference":[{"issue":"7","key":"6844_CR1","doi-asserted-by":"publisher","first-page":"9046","DOI":"10.1109\/TITS.2021.3090329","volume":"23","author":"F Sun","year":"2022","unstructured":"Sun F, Liu H, Zhang Y (2022) Integrated aircraft and passenger recovery with enhancements in modeling, solution algorithm, and intermodalism. IEEE T Intell Transp 23(7):9046\u20139061. https:\/\/doi.org\/10.1109\/TITS.2021.3090329","journal-title":"IEEE T Intell Transp"},{"issue":"01","key":"6844_CR2","doi-asserted-by":"publisher","first-page":"2350010","DOI":"10.1142\/S1752890923500101","volume":"17","author":"S Sargazi","year":"2024","unstructured":"Sargazi S, Ahmadzade H, Nehi MH, Sayareh J (2024) A simulated annealing algorithm for quay crane scheduling and assignment problem under uncertain conditions. J Uncert Syst 17(01):2350010. https:\/\/doi.org\/10.1142\/S1752890923500101","journal-title":"J Uncert Syst"},{"issue":"4","key":"6844_CR3","doi-asserted-by":"publisher","first-page":"499","DOI":"10.1080\/01441647.2020.1861123","volume":"41","author":"L Carvalho","year":"2020","unstructured":"Carvalho L, Sternberg A, Maia Gon\u00e7alves L, Beatriz Cruz A, Soares JA, Brand\u00e3o D, Carvalho D, Ogasawara E (2020) On the relevance of data science for flight delay research: a systematic review. Transp Rev 41(4):499\u2013528. https:\/\/doi.org\/10.1080\/01441647.2020.1861123","journal-title":"Transp Rev"},{"key":"6844_CR4","doi-asserted-by":"publisher","DOI":"10.1016\/j.trb.2024.103063","volume":"188","author":"L Huang","year":"2024","unstructured":"Huang L, Wang W, Su Y, Li FJ (2024) Integrated aircraft routing and cargo routing problem for combination airlines. Transportation Research Part B: Methodological 188:103063. https:\/\/doi.org\/10.1016\/j.trb.2024.103063","journal-title":"Transportation Research Part B: Methodological"},{"issue":"4","key":"6844_CR5","doi-asserted-by":"publisher","DOI":"10.3390\/aerospace8040113","volume":"8","author":"P Andrade","year":"2021","unstructured":"Andrade P, Silva C, Ribeiro B, Santos BF (2021) Aircraft maintenance check scheduling using reinforcement learning. Aerospace 8(4):113. https:\/\/doi.org\/10.3390\/aerospace8040113","journal-title":"Aerospace"},{"key":"6844_CR6","doi-asserted-by":"publisher","unstructured":"Y Kobayashi Y Fukuyama 2022 Parallel Reactive Tabu Search for Aircraft Maintenance Routing. In2022 IEEE Symposium Series on Computational Intelligence (SSCI) 2022 Dec 4 (pp. 1567-1573). IEEE https:\/\/doi.org\/10.1109\/SSCI51031.2022.10022148","DOI":"10.1109\/SSCI51031.2022.10022148"},{"issue":"6","key":"6844_CR7","doi-asserted-by":"publisher","first-page":"932","DOI":"10.1108\/AEAT-10-2022-0267","volume":"95","author":"X Chen","year":"2023","unstructured":"Chen X, Chu S, Zhang G, Chen X, Huang J, Yi M (2023) Prediction of the maintenance cost of general aviation aircraft based on engineering method. Aircr Eng Aerosp Tec 95(6):932\u2013938. https:\/\/doi.org\/10.1108\/AEAT-10-2022-0267","journal-title":"Aircr Eng Aerosp Tec"},{"key":"6844_CR8","doi-asserted-by":"publisher","DOI":"10.1016\/j.cor.2021.105551","volume":"137","author":"MB Ahmed","year":"2022","unstructured":"Ahmed MB, Hryhoryeva M, Hvattum LM, Haouari M (2022) A matheuristic for the robust integrated airline fleet assignment, aircraft routing, and crew pairing problem. Comput Oper Res 137:105551. https:\/\/doi.org\/10.1016\/j.cor.2021.105551","journal-title":"Comput Oper Res"},{"key":"6844_CR9","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2020.114399","volume":"169","author":"JH Ruan","year":"2021","unstructured":"Ruan JH, Wang ZX, Chan FT, Patnaik S, Tiwari MK (2021) A reinforcement learning-based algorithm for the aircraft maintenance routing problem. Expert Syst Appl 169:114399. https:\/\/doi.org\/10.1016\/j.eswa.2020.114399","journal-title":"Expert Syst Appl"},{"issue":"10","key":"6844_CR10","doi-asserted-by":"publisher","first-page":"1518","DOI":"10.1108\/AEAT-11-2022-0330","volume":"95","author":"G Liu","year":"2023","unstructured":"Liu G, Guo R, Chen J (2023) A scheduling model of civil aircraft maintenance stand based on spatiotemporal constraints. Aircr Eng Aerosp Tec 95(10):1518\u20131530","journal-title":"Aircr Eng Aerosp Tec"},{"key":"6844_CR11","doi-asserted-by":"publisher","DOI":"10.1016\/j.jairtraman.2022.102270","volume":"105","author":"X Wen","year":"2022","unstructured":"Wen X, Sun X, Ma HL, Sun Y (2022) A column generation approach for operational flight scheduling and aircraft maintenance routing. J Air Transp Manag 105:102270. https:\/\/doi.org\/10.1016\/j.jairtraman.2022.102270","journal-title":"J Air Transp Manag"},{"key":"6844_CR12","doi-asserted-by":"publisher","DOI":"10.1016\/j.tre.2023.103237","volume":"177","author":"YH He","year":"2023","unstructured":"He YH, Ma HL, Park WY, Liu SQ, Chung SH (2023) Maximizing robustness of aircraft routing with heterogeneous maintenance tasks. Transp Res E Logist Transp Rev 177:103237. https:\/\/doi.org\/10.1016\/j.tre.2023.103237","journal-title":"Transp Res E Logist Transp Rev"},{"key":"6844_CR13","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2024.104518","volume":"160","author":"Q Zhang","year":"2024","unstructured":"Zhang Q, Chung SH, Ma HL, Sun XT (2024) Robust aircraft maintenance routing with heterogeneous aircraft maintenance tasks. Transportation Research Part C: Emerging Technologies 160:104518. https:\/\/doi.org\/10.1016\/j.trc.2024.104518","journal-title":"Transportation Research Part C: Emerging Technologies"},{"key":"6844_CR14","doi-asserted-by":"publisher","unstructured":"Sciau JB, Goyon A, Sarazin A, Bascans J, C, Prud\u2019homme, X, Lorca (2024) Using constraint programming to address the operational aircraft line maintenance scheduling problem. J Air Transp Manag 115:102537. https:\/\/doi.org\/10.1016\/j.jairtraman.2024.102537","DOI":"10.1016\/j.jairtraman.2024.102537"},{"key":"6844_CR15","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2019.106045","volume":"137","author":"R Cui","year":"2019","unstructured":"Cui R, Dong X, Lin Y (2019) Models for aircraft maintenance routing problem with consideration of remaining time and robustness. Comput Ind Eng 137:106045. https:\/\/doi.org\/10.1016\/j.cie.2019.106045","journal-title":"Comput Ind Eng"},{"key":"6844_CR16","doi-asserted-by":"publisher","first-page":"346","DOI":"10.1016\/j.cie.2018.05.002","volume":"120","author":"AE Eltoukhy","year":"2018","unstructured":"Eltoukhy AE, Chan FT, Chung SH, Niu B (2018) A model with a solution algorithm for the operational aircraft maintenance routing problem. Comput Ind Eng 120:346\u2013359. https:\/\/doi.org\/10.1016\/j.cie.2018.05.002","journal-title":"Comput Ind Eng"},{"issue":"2024","key":"6844_CR17","doi-asserted-by":"publisher","first-page":"106545","DOI":"10.1016\/j.cor.2024.106545","volume":"164","author":"EE Yurek","year":"2024","unstructured":"Yurek EE (2024) Combinatorial Benders decomposition for the operational aircraft maintenance routing problem. Comput Oper Res 164(2024):106545. https:\/\/doi.org\/10.1016\/j.cor.2024.106545","journal-title":"Comput Oper Res"},{"issue":"331","key":"6844_CR18","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10489-025-06249-z","volume":"55","author":"XY Gao","year":"2025","unstructured":"Gao XY, Peng D, Yang YX, Huang FY, Yuan Y, Tan CD, Li FF (2025) Two-stage graph attention networks and Q-learning based maintenance tasks scheduling. Appl Intell 55(331):1\u201320. https:\/\/doi.org\/10.1007\/s10489-025-06249-z","journal-title":"Appl Intell"},{"issue":"1","key":"6844_CR19","doi-asserted-by":"publisher","first-page":"214","DOI":"10.1109\/TITS.2024.3452430","volume":"72","author":"MY Shang","year":"2023","unstructured":"Shang MY, Zhou YH, Mei YD, Zhao J, Fujita H (2023) IEEE T Veh Technol 72(1):214\u2013226. https:\/\/doi.org\/10.1109\/TITS.2024.3452430","journal-title":"IEEE T Veh Technol"},{"key":"6844_CR20","doi-asserted-by":"publisher","DOI":"10.1016\/j.jairtraman.2023.102397","volume":"109","author":"IL Geursen","year":"2023","unstructured":"Geursen IL, Santos BF, Yorke-Smith N (2023) Fleet planning under demand and fuel price uncertainty using actor-critic reinforcement learning. J Air Transp Manag 109:102397. https:\/\/doi.org\/10.1016\/j.jairtraman.2023.102397","journal-title":"J Air Transp Manag"},{"key":"6844_CR21","doi-asserted-by":"publisher","unstructured":"D, Si\u0307m\u015fek, MS, Akt\u00fcrk (2022) Resilient airline scheduling to minimize delay risks. Transport Res C Emer Technol 14:103734. https:\/\/doi.org\/10.1016\/j.trc.2022.103734","DOI":"10.1016\/j.trc.2022.103734"},{"key":"6844_CR22","doi-asserted-by":"publisher","unstructured":"Abuqaddom I, Mahafzah MA (2021) Oriented stochastic loss descent algorithm to train very deep multi-layer neural networks without vanishing gradients. Knowl-Based Syst 230:107391. https:\/\/doi.org\/10.1016\/j.knosys.2021.107391","DOI":"10.1016\/j.knosys.2021.107391"},{"key":"6844_CR23","doi-asserted-by":"publisher","first-page":"105667","DOI":"10.1016\/j.cor.2021.105667","volume":"141","author":"TVD Weide","year":"2022","unstructured":"Weide TVD, Deng Q, Santos BF (2022) Robust long-term aircraft heavy maintenance check scheduling optimization under uncertainty. Comput Opera Res 141:105667. https:\/\/doi.org\/10.1016\/j.cor.2021.105667","journal-title":"Comput Opera Res"},{"key":"6844_CR24","doi-asserted-by":"publisher","first-page":"62","DOI":"10.1016\/j.tre.2018.11.004","volume":"122","author":"CL Wu","year":"2019","unstructured":"Wu CL, Law K (2019) Modelling the delay propagation effects of multiple resource connections in an airline network using a Bayesian network model. Transp Res E Logist Transp Rev 122:62\u201377. https:\/\/doi.org\/10.1016\/j.tre.2018.11.004","journal-title":"Transp Res E Logist Transp Rev"},{"key":"6844_CR25","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2020.107056","volume":"153","author":"Y Hu","year":"2021","unstructured":"Hu Y, Miao X, Zhang J, Liu J, Pan E (2021) Reinforcement learning-driven maintenance strategy: a novel solution for long-term aircraft maintenance decision optimization. Comput Ind Eng 153:107056. https:\/\/doi.org\/10.1016\/j.cie.2020.107056","journal-title":"Comput Ind Eng"},{"issue":"4","key":"6844_CR26","doi-asserted-by":"publisher","first-page":"4063","DOI":"10.1007\/s10489-022-03605-1","volume":"53","author":"T Kravaris","year":"2023","unstructured":"Kravaris T, Lentzos K, Santipantakis G, Vouros GA, Andrienko G, Andrienko N, Crook I, Garcia JMC, Martinez EI (2023) Explaining deep reinforcement learning decisions in complex multiagent settings: towards enabling automation in air traffic flow management. Appl Intell 53(4):4063\u20134098. https:\/\/doi.org\/10.1007\/s10489-022-03605-1","journal-title":"Appl Intell"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-025-06844-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10489-025-06844-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-025-06844-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,26]],"date-time":"2025-11-26T08:04:49Z","timestamp":1764144289000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10489-025-06844-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,27]]},"references-count":26,"journal-issue":{"issue":"16","published-print":{"date-parts":[[2025,11]]}},"alternative-id":["6844"],"URL":"https:\/\/doi.org\/10.1007\/s10489-025-06844-0","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"type":"print","value":"0924-669X"},{"type":"electronic","value":"1573-7497"}],"subject":[],"published":{"date-parts":[[2025,10,27]]},"assertion":[{"value":"6 February 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 August 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 October 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"1053"}}