{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T02:21:32Z","timestamp":1781662892437,"version":"3.54.5"},"reference-count":54,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2026,2,9]],"date-time":"2026-02-09T00:00:00Z","timestamp":1770595200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100009950","name":"Ministry of Education","doi-asserted-by":"publisher","award":["2025-RISE-01-014-05"],"award-info":[{"award-number":["2025-RISE-01-014-05"]}],"id":[{"id":"10.13039\/100009950","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["RS-2023-00221365"],"award-info":[{"award-number":["RS-2023-00221365"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,2,28]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Efficient assembly line optimization is essential for improving productivity and cost competitiveness in modern manufacturing systems. Despite its importance, many existing approaches neglect the limited number of resources and workers available in real production environments, leading to solutions that are difficult to deploy in practice. This study proposes a hierarchical framework that tightly integrates human intent interpretation, logical system configuration, and physical layout optimization. A large language model fine-tuned with low-rank adaptation translates user-defined objectives and constraints expressed in natural language into quantitative optimization goals. Logical configurations are optimized using metaheuristic methods, while physical layouts are refined using implicit quantile network (IQN)\u2013based deep reinforcement learning. The IQN model captures the full return distribution through implicit quantile sampling, enabling more flexible policy learning under stochastic environments. Discrete-event simulation is used to evaluate key performance indicators and refine the system configuration. Simulation results demonstrate that the proposed framework generates feasible and robust assembly line designs with improved practical deployability.<\/jats:p>","DOI":"10.1093\/jcde\/qwag013","type":"journal-article","created":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T12:46:25Z","timestamp":1770381985000},"page":"23-45","source":"Crossref","is-referenced-by-count":1,"title":["User-friendly assembly line optimization: A hierarchical approach combining simulation-evaluated heuristics and reinforcement learning"],"prefix":"10.1093","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-3947-6916","authenticated-orcid":false,"given":"Ye Ji","family":"Choi","sequence":"first","affiliation":[{"name":"Seoul National University of Science and Technology Department of Applied Artificial Intelligence, , 232 Gongneung-ro, Nowon-gu, Seoul 01811 ,","place":["Republic of Korea"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2534-7353","authenticated-orcid":false,"given":"Byeong Soo","family":"Kim","sequence":"additional","affiliation":[{"name":"Seoul National University of Science and Technology Department of Applied Artificial Intelligence, , 232 Gongneung-ro, Nowon-gu, Seoul 01811 ,","place":["Republic of Korea"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2026,2,9]]},"reference":[{"key":"2026050910315063700_bib1","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2407.19633","article-title":"OptiMUS-0.3: Using large language models to model and solve optimization problems at scale","author":"Ahmadi-Teshnizi","year":"2024"},{"key":"2026050910315063700_bib2","doi-asserted-by":"publisher","first-page":"449","DOI":"10.1016\/j.engappai.2010.08.006","article-title":"A hybrid genetic algorithm for mixed model assembly line balancing problem with parallel workstations and zoning constraints","volume":"24","author":"Akp\u0131nar","year":"2011","journal-title":"Engineering Applications of Artificial Intelligence"},{"key":"2026050910315063700_bib3","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-41544-0","volume-title":"Tecnomatix Plant Simulation","author":"Bangsow","year":"2020"},{"key":"2026050910315063700_bib4","doi-asserted-by":"publisher","first-page":"259","DOI":"10.1016\/j.ijpe.2012.10.020","article-title":"A taxonomy of line balancing problems and their solutionapproaches","volume":"142","author":"Batta\u00efa","year":"2013","journal-title":"International Journal of Production Economics"},{"key":"2026050910315063700_bib5","doi-asserted-by":"publisher","first-page":"694","DOI":"10.1016\/j.ejor.2004.07.023","article-title":"A survey on problems and methods in generalized assembly line balancing","volume":"168","author":"Becker","year":"2006","journal-title":"European Journal of Operational Research"},{"key":"2026050910315063700_bib6","doi-asserted-by":"publisher","first-page":"674","DOI":"10.1016\/j.ejor.2006.10.010","article-title":"A classification of assembly line balancing problems","volume":"183","author":"Boysen","year":"2007","journal-title":"European Journal of Operational Research"},{"key":"2026050910315063700_bib7","doi-asserted-by":"publisher","first-page":"509","DOI":"10.1016\/j.ijpe.2007.02.026","article-title":"Assembly line balancing: Which model to use when?","volume":"111","author":"Boysen","year":"2008","journal-title":"International Journal of Production Economics"},{"key":"2026050910315063700_bib8","doi-asserted-by":"publisher","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"},{"key":"2026050910315063700_bib9","doi-asserted-by":"publisher","first-page":"3503","DOI":"10.1080\/00207540701197010","article-title":"ASALBP: The alternative subgraphs assembly line balancing problem","volume":"46","author":"Capacho","year":"2008","journal-title":"International Journal of Production Research"},{"key":"2026050910315063700_bib10","author":"Chan","year":"1993","journal-title":"Facility Layout and Location: An Analytical Approach. 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