{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T17:07:55Z","timestamp":1773335275553,"version":"3.50.1"},"reference-count":43,"publisher":"Elsevier BV","issue":"1","license":[{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,12,10]],"date-time":"2025-12-10T00:00:00Z","timestamp":1765324800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["European Journal of Operational Research"],"published-print":{"date-parts":[[2026,7]]},"DOI":"10.1016\/j.ejor.2025.12.017","type":"journal-article","created":{"date-parts":[[2025,12,11]],"date-time":"2025-12-11T17:21:45Z","timestamp":1765473705000},"page":"52-65","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"title":["Solving the paint shop problem with flexible management of multi-lane buffers using reinforcement learning and action masking"],"prefix":"10.1016","volume":"332","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-6767-3981","authenticated-orcid":false,"given":"Mirko","family":"Stappert","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2562-6344","authenticated-orcid":false,"given":"Bernhard","family":"Lutz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6315-1138","authenticated-orcid":false,"given":"Janis","family":"Brammer","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2178-3705","authenticated-orcid":false,"given":"Dirk","family":"Neumann","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"issue":"2","key":"10.1016\/j.ejor.2025.12.017_bib0001","doi-asserted-by":"crossref","first-page":"405","DOI":"10.1016\/j.ejor.2020.07.063","article-title":"Machine learning for combinatorial optimization: A methodological tour d\u2019horizon","volume":"290","author":"Bengio","year":"2021","journal-title":"European Journal of Operational Research"},{"issue":"2","key":"10.1016\/j.ejor.2025.12.017_bib0002","doi-asserted-by":"crossref","first-page":"276","DOI":"10.1007\/BF03342757","article-title":"The car resequencing problem with pull-off tables","volume":"4","author":"Boysen","year":"2011","journal-title":"Business Research"},{"issue":"3","key":"10.1016\/j.ejor.2025.12.017_bib0003","doi-asserted-by":"crossref","first-page":"594","DOI":"10.1016\/j.ejor.2011.08.009","article-title":"Resequencing of mixed-model assembly lines: Survey and research agenda","volume":"216","author":"Boysen","year":"2012","journal-title":"European Journal of Operational Research"},{"issue":"3","key":"10.1016\/j.ejor.2025.12.017_bib0004","doi-asserted-by":"crossref","first-page":"797","DOI":"10.1016\/j.ejor.2021.11.043","article-title":"Assembly line balancing: What happened in the last fifteen years?","volume":"301","author":"Boysen","year":"2022","journal-title":"European Journal of Operational Research"},{"issue":"1","key":"10.1016\/j.ejor.2025.12.017_bib0005","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1016\/j.cor.2012.05.012","article-title":"A decomposition approach for the car resequencing problem with selectivity banks","volume":"40","author":"Boysen","year":"2013","journal-title":"Computers & Operations Research"},{"key":"10.1016\/j.ejor.2025.12.017_bib0006","doi-asserted-by":"crossref","DOI":"10.1016\/j.cie.2021.107704","article-title":"Solving the mixed model sequencing problem with reinforcement learning and metaheuristics","volume":"162","author":"Brammer","year":"2021","journal-title":"Computers & Industrial Engineering"},{"issue":"1","key":"10.1016\/j.ejor.2025.12.017_bib0007","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/j.ejor.2021.08.007","article-title":"Permutation flow shop scheduling with multiple lines and demand plans using reinforcement learning","volume":"299","author":"Brammer","year":"2022","journal-title":"European Journal of Operational Research"},{"issue":"1","key":"10.1016\/j.ejor.2025.12.017_bib0008","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1007\/s00291-021-00652-x","article-title":"Stochastic mixed model sequencing with multiple stations using reinforcement learning and probability quantiles","volume":"44","author":"Brammer","year":"2022","journal-title":"OR Spectrum"},{"key":"10.1016\/j.ejor.2025.12.017_bib0009","unstructured":"Brockman, G., Cheung, V., Pettersson, L., Schneider, J., Schulman, J., Tang, J., & Zaremba, W. (2016). OpenAI gym. Available at https:\/\/arxiv.org\/abs\/1606.01540."},{"key":"10.1016\/j.ejor.2025.12.017_bib0010","doi-asserted-by":"crossref","DOI":"10.1016\/j.cie.2018.11.056","article-title":"Automotive paint shop 4.0","volume":"139","author":"Bysko","year":"2020","journal-title":"Computers & Industrial Engineering"},{"issue":"3","key":"10.1016\/j.ejor.2025.12.017_bib0011","doi-asserted-by":"crossref","first-page":"1037","DOI":"10.1007\/s10845-023-02079-3","article-title":"Nash equilibrium as a tool for the car sequencing problem 4.0","volume":"35","author":"Bysko","year":"2024","journal-title":"Journal of Intelligent Manufacturing"},{"issue":"8","key":"10.1016\/j.ejor.2025.12.017_bib0012","doi-asserted-by":"crossref","first-page":"1525","DOI":"10.1080\/00207540310001645156","article-title":"Sequence alteration and restoration related to sequenced parts delivery on an automobile mixed-model assembly line with multiple departments","volume":"42","author":"Ding","year":"2004","journal-title":"International Journal of Production Research"},{"key":"10.1016\/j.ejor.2025.12.017_bib0013","series-title":"Operations research proceedings 2002","first-page":"235","article-title":"Sorting with line storage systems","author":"Epping","year":"2003"},{"issue":"200","key":"10.1016\/j.ejor.2025.12.017_bib0014","doi-asserted-by":"crossref","first-page":"675","DOI":"10.1080\/01621459.1937.10503522","article-title":"The use of ranks to avoid the assumption of normality implicit in the analysis of variance","volume":"32","author":"Friedman","year":"1937","journal-title":"Journal of the American Statistical Association"},{"key":"10.1016\/j.ejor.2025.12.017_bib0015","series-title":"Handbook of Metaheuristics","volume":"vol. 272","author":"Gendreau","year":"2018"},{"issue":"2","key":"10.1016\/j.ejor.2025.12.017_bib0016","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1016\/j.ejor.2014.09.031","article-title":"A priori policy evaluation and cyclic-order-based simulated annealing for the multi-compartment vehicle routing problem with stochastic demands","volume":"241","author":"Goodson","year":"2015","journal-title":"European Journal of Operational Research"},{"issue":"10","key":"10.1016\/j.ejor.2025.12.017_bib0017","doi-asserted-by":"crossref","first-page":"2897","DOI":"10.1080\/00207543.2016.1227101","article-title":"A stochastic programming model for resequencing buffer content optimisation in mixed-model assembly lines","volume":"55","author":"Gunay","year":"2017","journal-title":"International Journal of Production Research"},{"key":"10.1016\/j.ejor.2025.12.017_bib0018","unstructured":"Gurobi Optimization, L. (2023). Gurobi optimizer reference manual. Available athttps:\/\/www.gurobi.com."},{"key":"10.1016\/j.ejor.2025.12.017_bib0019","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1016\/j.apm.2018.07.035","article-title":"Accelerated dynamic programming algorithms for a car resequencing problem in automotive paint shops","volume":"64","author":"Hong","year":"2018","journal-title":"Applied Mathematical Modelling"},{"issue":"7","key":"10.1016\/j.ejor.2025.12.017_bib0020","doi-asserted-by":"crossref","first-page":"2363","DOI":"10.1080\/00207543.2024.2403112","article-title":"Deep reinforcement learning for solving car resequencing with selectivity banks in automotive assembly shops","volume":"63","author":"Huang","year":"2025","journal-title":"International Journal of Production Research"},{"issue":"16","key":"10.1016\/j.ejor.2025.12.017_bib0021","doi-asserted-by":"crossref","first-page":"3831","DOI":"10.1080\/00207540310001595792","article-title":"Algorithm for agile assembling-to-order in the automotive industry","volume":"41","author":"Inman","year":"2003","journal-title":"International Journal of Production Research"},{"issue":"1","key":"10.1016\/j.ejor.2025.12.017_bib0022","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1016\/j.ejor.2017.04.050","article-title":"A batch-oblivious approach for complex job-shop scheduling problems","volume":"263","author":"Knopp","year":"2017","journal-title":"European Journal of Operational Research"},{"key":"10.1016\/j.ejor.2025.12.017_bib0023","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1016\/j.cor.2016.04.019","article-title":"Paint batching problem on M-to-1 conveyor systems","volume":"74","author":"Ko","year":"2016","journal-title":"Computers & Operations Research"},{"issue":"1","key":"10.1016\/j.ejor.2025.12.017_bib0024","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1109\/TRA.2002.807556","article-title":"Resequencing and feature assignment on an automated assembly line","volume":"19","author":"Lahmar","year":"2003","journal-title":"IEEE Transactions on Robotics and Automation"},{"key":"10.1016\/j.ejor.2025.12.017_bib0025","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1016\/j.jmsy.2020.06.001","article-title":"Deep reinforcement learning for a color-batching resequencing problem","volume":"56","author":"Leng","year":"2020","journal-title":"Journal of Manufacturing Systems"},{"issue":"15","key":"10.1016\/j.ejor.2025.12.017_bib0026","doi-asserted-by":"crossref","first-page":"5156","DOI":"10.1080\/00207543.2022.2098871","article-title":"A multi-objective reinforcement learning approach for resequencing scheduling problems in automotive manufacturing systems","volume":"61","author":"Leng","year":"2023","journal-title":"International Journal of Production Research"},{"key":"10.1016\/j.ejor.2025.12.017_bib0027","series-title":"International conference on industrial engineering and engineering management","first-page":"658","article-title":"A research of resequencing problem in automobile paint shops using selectivity banks","author":"Lin","year":"2011"},{"issue":"2","key":"10.1016\/j.ejor.2025.12.017_bib0028","doi-asserted-by":"crossref","first-page":"530","DOI":"10.1016\/j.ejor.2019.09.021","article-title":"Stochastic mixed-model assembly line sequencing problem: Mathematical modeling and Q-learning based simulated annealing hyper-heuristics","volume":"282","author":"Mosadegh","year":"2020","journal-title":"European Journal of Operational Research"},{"key":"10.1016\/j.ejor.2025.12.017_bib0029","series-title":"Distribution-free multiple comparisons","author":"Nemenyi","year":"1963"},{"issue":"1","key":"10.1016\/j.ejor.2025.12.017_bib0030","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.ejor.2022.08.009","article-title":"A systematic review of multi-objective hybrid flow shop scheduling","volume":"309","author":"Neufeld","year":"2023","journal-title":"European Journal of Operational Research"},{"issue":"13","key":"10.1016\/j.ejor.2025.12.017_bib0031","doi-asserted-by":"crossref","first-page":"4316","DOI":"10.1080\/00207543.2021.1973138","article-title":"Deep reinforcement learning in production systems: A systematic literature review","volume":"60","author":"Panzer","year":"2022","journal-title":"International Journal of Production Research"},{"issue":"2","key":"10.1016\/j.ejor.2025.12.017_bib0032","doi-asserted-by":"crossref","first-page":"338","DOI":"10.1016\/S0377-2217(02)00073-5","article-title":"Formulating logical implications in combinatorial optimisation","volume":"140","author":"Plastria","year":"2002","journal-title":"European Journal of Operational Research"},{"issue":"268","key":"10.1016\/j.ejor.2025.12.017_bib0033","first-page":"1","article-title":"Stable-baselines3: Reliable reinforcement learning implementations","volume":"22","author":"Raffin","year":"2021","journal-title":"Journal of Machine Learning Research"},{"key":"10.1016\/j.ejor.2025.12.017_bib0034","unstructured":"Schulman, J., Moritz, P., Levine, S., Jordan, M., & Abbeel, P. (2015). High-dimensional continuous control using generalized advantage estimation. arXiv preprint, https:\/\/arxiv.org\/abs\/1506.02438."},{"key":"10.1016\/j.ejor.2025.12.017_bib0035","unstructured":"Schulman, J., Wolski, F., Dhariwal, P., Radford, A., & Klimov, O. (2017). Proximal policy optimization algorithms. arXiv preprint, https:\/\/arxiv.org\/abs\/1707.06347."},{"issue":"9","key":"10.1016\/j.ejor.2025.12.017_bib0036","doi-asserted-by":"crossref","first-page":"1865","DOI":"10.1080\/00207540310001646821","article-title":"A sequential ordering problem in automotive paint shops","volume":"42","author":"Spieckermann","year":"2004","journal-title":"International Journal of Production Research"},{"key":"10.1016\/j.ejor.2025.12.017_bib0037","unstructured":"Stappert, M., Lutz, B., Brammer, J., & Neumann, D. (2023). Data for: Solving the paint shop problem using reinforcement learning. Dataset on Mendeley. Available at10.17632\/zbg64f6vb3.1."},{"key":"10.1016\/j.ejor.2025.12.017_bib0038","doi-asserted-by":"crossref","DOI":"10.1016\/j.cie.2024.109990","article-title":"Integrating virtual resequencing with car resequencing via selectivity banks for mixed-model assembly lines","volume":"189","author":"Sun","year":"2024","journal-title":"Computers & Industrial Engineering"},{"issue":"4","key":"10.1016\/j.ejor.2025.12.017_bib0039","doi-asserted-by":"crossref","first-page":"1124","DOI":"10.1080\/00207543.2014.948970","article-title":"A colour-batching problem using selectivity banks in automobile paint shops","volume":"53","author":"Sun","year":"2015","journal-title":"International Journal of Production Research"},{"key":"10.1016\/j.ejor.2025.12.017_bib0040","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1016\/j.jmsy.2017.04.019","article-title":"A study on implementing color-batching with selectivity banks in automotive paint shops","volume":"44","author":"Sun","year":"2017","journal-title":"Journal of Manufacturing Systems"},{"key":"10.1016\/j.ejor.2025.12.017_bib0041","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1016\/j.omega.2017.11.006","article-title":"Resequencing mixed-model assembly lines with restoration to customer orders","volume":"78","author":"Taube","year":"2018","journal-title":"Omega"},{"key":"10.1016\/j.ejor.2025.12.017_bib0042","doi-asserted-by":"crossref","first-page":"36","DOI":"10.37610\/dyo.v0i54.458","article-title":"Solving the car resequencing problem with mix banks","volume":"54","author":"Valero-Herrero","year":"2014","journal-title":"Direcci\u00f3n y Organizaci\u00f3n"},{"key":"10.1016\/j.ejor.2025.12.017_bib0043","doi-asserted-by":"crossref","DOI":"10.1016\/j.cie.2020.107008","article-title":"Mathematical modeling and heuristic approaches for a multi-stage car sequencing problem","volume":"152","author":"Wu","year":"2021","journal-title":"Computers & Industrial Engineering"}],"container-title":["European Journal of Operational Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0377221725009841?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0377221725009841?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T05:31:13Z","timestamp":1773293473000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0377221725009841"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7]]},"references-count":43,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,7]]}},"alternative-id":["S0377221725009841"],"URL":"https:\/\/doi.org\/10.1016\/j.ejor.2025.12.017","relation":{},"ISSN":["0377-2217"],"issn-type":[{"value":"0377-2217","type":"print"}],"subject":[],"published":{"date-parts":[[2026,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Solving the paint shop problem with flexible management of multi-lane buffers using reinforcement learning and action masking","name":"articletitle","label":"Article Title"},{"value":"European Journal of Operational Research","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ejor.2025.12.017","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 The Author(s). Published by Elsevier B.V.","name":"copyright","label":"Copyright"}]}}