{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T23:48:47Z","timestamp":1791935327213,"version":"4.3.4"},"reference-count":71,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2027,1,1]],"date-time":"2027-01-01T00:00:00Z","timestamp":1798761600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Expert Systems with Applications"],"published-print":{"date-parts":[[2027,1]]},"DOI":"10.1016\/j.eswa.2026.133570","type":"journal-article","created":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T06:38:44Z","timestamp":1783751924000},"page":"133570","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":1,"special_numbering":"PB","title":["Deep reinforcement learning\u2013driven space decomposition variable neighborhood search algorithm for distributed heterogeneous factory lot-sizing and scheduling problem"],"prefix":"10.1016","volume":"332","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-2698-9484","authenticated-orcid":false,"given":"Feng-Shun","family":"Zhou","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0048-1487","authenticated-orcid":false,"given":"Bin","family":"Qian","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5000-6625","authenticated-orcid":false,"given":"Rong","family":"Hu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jun-Qing","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huai-Ping","family":"Jin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zi-Qi","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8953-1550","authenticated-orcid":false,"given":"Jian-Bo","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.eswa.2026.133570_b0005","doi-asserted-by":"crossref","first-page":"353","DOI":"10.1016\/j.ejor.2013.02.052","article-title":"The single item uncapacitated lot-sizing problem with time-dependent batch sizes: NP-hard and polynomial cases","volume":"229","author":"Akbalik","year":"2013","journal-title":"European Journal of Operational Research"},{"key":"10.1016\/j.eswa.2026.133570_b0010","article-title":"Energy-efficient distributed heterogeneous hybrid flow-shop scheduling using graph neural network and deep reinforcement learning","volume":"1\u20131","author":"Bao","year":"2025","journal-title":"IEEE Transactions on Automation Science and Engineering"},{"key":"10.1016\/j.eswa.2026.133570_b0015","doi-asserted-by":"crossref","first-page":"296","DOI":"10.1057\/palgrave.jors.2602016","article-title":"Lot streaming with variable sublots: An integer programming formulation","volume":"57","author":"Biskup","year":"2006","journal-title":"The Journal of the Operational Research Society"},{"key":"10.1016\/j.eswa.2026.133570_b0020","doi-asserted-by":"crossref","first-page":"353","DOI":"10.1023\/A:1020499411651","article-title":"Generalized hamming distance","author":"Bookstein","year":"2002","journal-title":"Information Retrieval"},{"key":"10.1016\/j.eswa.2026.133570_b0025","doi-asserted-by":"crossref","first-page":"444","DOI":"10.1287\/opre.48.3.444.12431","article-title":"Improvements and comparison of heuristics for solving the uncapacitated multisource weber problem","volume":"48","author":"Brimberg","year":"2000","journal-title":"Operations Research"},{"key":"10.1016\/j.eswa.2026.133570_b0030","doi-asserted-by":"crossref","DOI":"10.4108\/eai.13-7-2018.163925","article-title":"Kendall tau sequence distance: Extending kendall tau from ranks to sequences","volume":"7","author":"Cicirello","year":"2020","journal-title":"EAI Endorsed Transactions on Industrial Networks and Intelligent Systems"},{"key":"10.1016\/j.eswa.2026.133570_b0035","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1016\/S1045-926X(02)00060-5","article-title":"Applying software visualization technology to support the use of evolutionary algorithms","volume":"14","author":"Collins","year":"2003","journal-title":"Journal of Visual Languages and Computing"},{"key":"10.1016\/j.eswa.2026.133570_b0040","doi-asserted-by":"crossref","first-page":"190","DOI":"10.3390\/info16030190","article-title":"Bridging the gap between theory and practice: Fitness landscape analysis of real-world problems with nearest-better network","volume":"16","author":"Diao","year":"2025","journal-title":"Information"},{"key":"10.1016\/j.eswa.2026.133570_b0045","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2021.115903","article-title":"A speed-up procedure for the hybrid flow shop scheduling problem","volume":"187","author":"Fernandez-Viagas","year":"2022","journal-title":"Expert Systems with Applications"},{"key":"10.1016\/j.eswa.2026.133570_b0050","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/j.ijpe.2013.12.009","article-title":"The lot sizing problem: A tertiary study","volume":"155","author":"Glock","year":"2014","journal-title":"International Journal of Production Economics"},{"key":"10.1016\/j.eswa.2026.133570_b0055","series-title":"2023 13th international conference on advanced computer information technologies (ACIT). Presented at the 2023 13th international conference on advanced computer information technologies (ACIT), IEEE, Wroc\u0142aw, Poland","first-page":"126","article-title":"Visualizing feasible regions for optimization problems on high-dimensional permutations using dimensionality reduction methods","author":"Grebennik","year":"2023"},{"key":"10.1016\/j.eswa.2026.133570_b0060","doi-asserted-by":"crossref","DOI":"10.1016\/j.cie.2023.109255","article-title":"Dynamic scheduling for flexible job shop using a deep reinforcement learning approach","volume":"180","author":"Gui","year":"2023","journal-title":"Computers and Industrial Engineering"},{"key":"10.1016\/j.eswa.2026.133570_b0065","doi-asserted-by":"crossref","DOI":"10.1016\/j.cie.2022.108745","article-title":"Lot streaming in hybrid flowshop scheduling problem by considering equal and consistent sublots under machine capability and limited waiting time constraint","volume":"173","author":"G\u00fcrsoy Y\u0131lmaz","year":"2022","journal-title":"Computers and Industrial Engineering"},{"key":"10.1016\/j.eswa.2026.133570_b0070","doi-asserted-by":"crossref","first-page":"186474","DOI":"10.1109\/ACCESS.2020.3029868","article-title":"Research on adaptive job shop scheduling problems based on dueling double DQN","volume":"8","author":"Han","year":"2020","journal-title":"IEEE Access"},{"key":"10.1016\/j.eswa.2026.133570_b0075","doi-asserted-by":"crossref","DOI":"10.1016\/j.swevo.2024.101498","article-title":"Collaborative Q-learning hyper-heuristic evolutionary algorithm for the production and transportation integrated scheduling of silicon electrodes","volume":"86","author":"Hu","year":"2024","journal-title":"Swarm and Evolutionary Computation"},{"key":"10.1016\/j.eswa.2026.133570_b0080","series-title":"Design and analysis of experiments with R","author":"John","year":"2014"},{"key":"10.1016\/j.eswa.2026.133570_b0085","series-title":"in: 2015 IEEE congress on evolutionary computation (CEC). Presented at the 2015 IEEE congress on evolutionary computation (CEC), IEEE, Sendai, Japan","first-page":"179","article-title":"SwarmViz: An open-source visualization tool for Particle Swarm Optimization","author":"Jornod","year":"2015"},{"key":"10.1016\/j.eswa.2026.133570_b0090","doi-asserted-by":"crossref","first-page":"577","DOI":"10.1016\/S0305-0483(01)00046-9","article-title":"A near-optimal heuristic for the sequencing problem in multiple-batch &ow-shops with small equal sublots","volume":"6","author":"Kalir","year":"2001","journal-title":"Omega"},{"key":"10.1016\/j.eswa.2026.133570_b0095","doi-asserted-by":"crossref","first-page":"144","DOI":"10.3390\/computation13060144","article-title":"Scalable clustering of complex ECG health data: Big data clustering analysis with UMAP and HDBSCAN","volume":"13","author":"Kaverinskiy","year":"2025","journal-title":"Computation"},{"key":"10.1016\/j.eswa.2026.133570_b0100","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2025.114549","article-title":"Dynamic scheduling for distributed flexible job shop using deep reinforcement learning","volume":"190","author":"Lei","year":"2026","journal-title":"Applied Soft Computing"},{"key":"10.1016\/j.eswa.2026.133570_b0105","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2024.112650","article-title":"A novel multi-objective hybrid evolutionary algorithm based on variable weight strategy for distributed hybrid flowshop scheduling with batch processing machines and variable sublots","volume":"170","author":"Li","year":"2025","journal-title":"Applied Soft Computing"},{"key":"10.1016\/j.eswa.2026.133570_b0110","unstructured":"Li, H., Zhang, H., He, Z., Jia, Y., Jiang, B., Huang, X., Ge, D. (2024). Solving integrated process planning and scheduling problem via graph neural network based deep reinforcement learning. https:\/\/doi.org\/10.48550\/arXiv.2409.00968."},{"key":"10.1016\/j.eswa.2026.133570_b0115","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1016\/j.asoc.2014.07.005","article-title":"A hybrid variable neighborhood search for solving the hybrid flow shop scheduling problem","volume":"24","author":"Li","year":"2014","journal-title":"Applied Soft Computing"},{"key":"10.1016\/j.eswa.2026.133570_b0120","doi-asserted-by":"crossref","DOI":"10.1016\/j.swevo.2019.100600","article-title":"Efficient multi-objective algorithm for the lot-streaming hybrid flowshop with variable sub-lots","volume":"52","author":"Li","year":"2020","journal-title":"Swarm and Evolutionary Computation"},{"key":"10.1016\/j.eswa.2026.133570_b0125","doi-asserted-by":"crossref","DOI":"10.1016\/j.cie.2021.107928","article-title":"Research on discrete intelligent workshop lot-streaming scheduling with variable sublots under engineer to order","volume":"165","author":"Li","year":"2022","journal-title":"Computers and Industrial Engineering"},{"key":"10.1016\/j.eswa.2026.133570_b0130","doi-asserted-by":"crossref","DOI":"10.1016\/j.rcim.2021.102283","article-title":"Real-time data-driven dynamic scheduling for flexible job shop with insufficient transportation resources using hybrid deep Q network","volume":"74","author":"Li","year":"2022","journal-title":"Robotics and Computer-Integrated Manufacturing"},{"key":"10.1016\/j.eswa.2026.133570_b0135","doi-asserted-by":"crossref","DOI":"10.1016\/j.cie.2024.110381","article-title":"Active learning based hyper-heuristic for the integration of production and transportation: A third-party logistics perspective","volume":"194","author":"Li","year":"2024","journal-title":"Computers and Industrial Engineering"},{"key":"10.1016\/j.eswa.2026.133570_b0140","first-page":"1","article-title":"Q-Learning-enhanced reconstructed discrete particle swarm optimization for distributed hybrid flowsh","author":"Liu","year":"2025","journal-title":"Engineering Optimization"},{"key":"10.1016\/j.eswa.2026.133570_b0145","doi-asserted-by":"crossref","first-page":"662","DOI":"10.1007\/s00170-002-1516-7","article-title":"A heuristic method for discrete lot streaming with variable sublots in a flow shop","volume":"22","author":"Liu","year":"2003","journal-title":"International Journal of Advanced Manufacturing Technology"},{"key":"10.1016\/j.eswa.2026.133570_b0150","doi-asserted-by":"crossref","DOI":"10.1016\/j.swevo.2024.101731","article-title":"Combining meta-heuristics and Q-learning for scheduling lot-streaming hybrid flow shops with consistent sublots","volume":"91","author":"Lu","year":"2024","journal-title":"Swarm and Evolutionary Computation"},{"key":"10.1016\/j.eswa.2026.133570_b0155","doi-asserted-by":"crossref","first-page":"2808","DOI":"10.3390\/s23052808","article-title":"A heuristic-based adaptive iterated greedy algorithm for lot-streaming hybrid flow shop scheduling problem with consistent and intermingled sub-lots","volume":"23","author":"Lu","year":"2023","journal-title":"Sensors"},{"key":"10.1016\/j.eswa.2026.133570_b0160","series-title":"Artificial evolution, lecture notes in computer science","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1007\/978-3-642-35533-2_6","article-title":"Visual analysis of population scatterplots","author":"Lutton","year":"2012"},{"key":"10.1016\/j.eswa.2026.133570_b0165","series-title":"Proceedings of the fifth Berkeley symposium on mathematical statistics & probability","first-page":"281","article-title":"Some methods of classification and analysis of multivariate observations","author":"Macqueen","year":"1967"},{"key":"10.1016\/j.eswa.2026.133570_b0170","series-title":"Recent advances in the theory and application of fitness landscapes, emergence, complexity and computation","first-page":"103","article-title":"Fitness landscape analysis for metaheuristic performance prediction","author":"Malan","year":"2014"},{"key":"10.1016\/j.eswa.2026.133570_b0175","doi-asserted-by":"crossref","unstructured":"McInnes, L., Healy, J., Melville, J., 2018. UMAP: Uniform manifold approximation and projection for dimension reduction.","DOI":"10.21105\/joss.00861"},{"key":"10.1016\/j.eswa.2026.133570_b0180","doi-asserted-by":"crossref","first-page":"232","DOI":"10.1109\/TEVC.2018.2846636","article-title":"Low-dimensional euclidean embedding for visualization of search spaces in combinatorial optimization","volume":"23","author":"Michalak","year":"2019","journal-title":"IEEE Transactions on Evolutionary Computation: A Publication of the IEEE Neural Networks Council"},{"key":"10.1016\/j.eswa.2026.133570_b0185","doi-asserted-by":"crossref","DOI":"10.1016\/j.scitotenv.2021.152365","article-title":"The application of Uniform Manifold Approximation and Projection (UMAP) for unconstrained ordination and classification of biological indicators in aquatic ecology","volume":"815","author":"Milo\u0161evi\u0107","year":"2022","journal-title":"The Science of the Total Environment"},{"key":"10.1016\/j.eswa.2026.133570_b0190","doi-asserted-by":"crossref","first-page":"1097","DOI":"10.1016\/S0305-0548(97)00031-2","article-title":"Variable neighborhood search","volume":"24","author":"Mladenovi\u0107","year":"1997","journal-title":"Computers and Operations Research"},{"key":"10.1016\/j.eswa.2026.133570_b0195","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2013\/216595","article-title":"Integration of lot sizing and flow shop scheduling with lot streaming","volume":"2013","author":"Mortezaei","year":"2013","journal-title":"Journal of Applied Mathematics"},{"key":"10.1016\/j.eswa.2026.133570_b0200","doi-asserted-by":"crossref","unstructured":"Na, S., Xumin, L., Yong, G., 2010. Research on k-means clustering algorithm: An improved k-means clustering algorithm. In: 2010 third international symposium on intelligent information technology and security informatics. Presented at the 2010 third international symposium on intelligent information technology and security informatics (IITSI), IEEE, Jian, China, pp. 63\u201367. https:\/\/doi.org\/10.1109\/IITSI.2010.74.","DOI":"10.1109\/IITSI.2010.74"},{"key":"10.1016\/j.eswa.2026.133570_b0205","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"},{"key":"10.1016\/j.eswa.2026.133570_b0210","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1016\/j.swevo.2019.01.002","article-title":"A multi-start variable neighbourhood descent algorithm for hybrid flowshop rescheduling","volume":"45","author":"Peng","year":"2019","journal-title":"Swarm and Evolutionary Computation"},{"key":"10.1016\/j.eswa.2026.133570_b0215","doi-asserted-by":"crossref","first-page":"1492","DOI":"10.1109\/TSMC.2022.3198829","article-title":"A matrix-cube-based estimation of distribution algorithm for no-wait flow-shop scheduling with sequence-dependent setup times and release times","volume":"53","author":"Qian","year":"2023","journal-title":"IEEE Transactions on Systems, Man, and Cybernetics: Systems"},{"key":"10.1016\/j.eswa.2026.133570_b0220","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2022.117256","article-title":"A collaborative iterative greedy algorithm for the scheduling of distributed heterogeneous hybrid flow shop with blocking constraints","volume":"201","author":"Qin","year":"2022","journal-title":"Expert Systems with Applications"},{"key":"10.1016\/j.eswa.2026.133570_b0225","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1007\/s10479-022-04701-8","article-title":"GRASP and VNS approaches for a vehicle routing problem with step cost functions","volume":"350","author":"Ronconi","year":"2025","journal-title":"Annals of Operations Research"},{"key":"10.1016\/j.eswa.2026.133570_b0230","doi-asserted-by":"crossref","DOI":"10.1016\/j.tre.2021.102293","article-title":"A hybrid variable neighborhood search approach for the multi-depot green vehicle routing problem","volume":"149","author":"Sadati","year":"2021","journal-title":"Transportation Research Part E: Logistics and Transportation Review"},{"key":"10.1016\/j.eswa.2026.133570_b0235","first-page":"6483","article-title":"Lot sizing and scheduling problem in distributed heterogeneous hybrid flow shop and learning-driven iterated local search algorithm","volume":"4","author":"Shao","year":"2023","journal-title":"IEEE Transactions on Automation Science and Engineering"},{"key":"10.1016\/j.eswa.2026.133570_b0240","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2025.103195","article-title":"Production-logistics collaborative scheduling in dynamic flexible job shops using nested-hierarchical deep reinforcement learning","volume":"65","author":"Shi","year":"2025","journal-title":"Advanced Engineering Informatics"},{"key":"10.1016\/j.eswa.2026.133570_b0245","doi-asserted-by":"crossref","first-page":"695","DOI":"10.1080\/07408179908969869","article-title":"Lot streaming and scheduling multiple products in two-machine no-wait flowshops","volume":"31","author":"Sriskandarajah","year":"1999","journal-title":"IIE Transactions"},{"key":"10.1016\/j.eswa.2026.133570_b0250","doi-asserted-by":"crossref","DOI":"10.1016\/j.cor.2024.106659","article-title":"Iterated variable neighborhood search for integrated scheduling of additive manufacturing and multi-trip vehicle routing problem","volume":"167","author":"Sugianto","year":"2024","journal-title":"Computers and Operations Research"},{"key":"10.1016\/j.eswa.2026.133570_b0255","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2022.119359","article-title":"Hybrid genetic algorithm with variable neighborhood search for flexible job shop scheduling problem in a machining system","volume":"215","author":"Sun","year":"2023","journal-title":"Expert Systems with Applications"},{"key":"10.1016\/j.eswa.2026.133570_b0260","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1016\/0377-2217(90)90090-X","article-title":"Some efficient heuristic methods for the flow shop sequencing problem","volume":"47","author":"Taillard","year":"1990","journal-title":"European Journal of Operational Research"},{"key":"10.1016\/j.eswa.2026.133570_b0265","doi-asserted-by":"crossref","first-page":"1275","DOI":"10.1080\/00207543.2024.2373426","article-title":"Integrated scheduling of multi-objective lot-streaming hybrid flowshop with AGV based on deep reinforcement learning","volume":"63","author":"Tang","year":"2025","journal-title":"International Journal of Production Research"},{"key":"10.1016\/j.eswa.2026.133570_b0270","doi-asserted-by":"crossref","first-page":"589","DOI":"10.1109\/TEVC.2024.3443874","article-title":"An iterated greedy algorithm with reinforcement learning for distributed hybrid flowshop problems with job merging","volume":"29","author":"Tao","year":"2025","journal-title":"IEEE Transactions on Evolutionary Computation: A Publication of the IEEE Neural Networks Council"},{"key":"10.1016\/j.eswa.2026.133570_b0275","doi-asserted-by":"crossref","first-page":"666","DOI":"10.1016\/j.ejor.2014.07.033","article-title":"New hard benchmark for flowshop scheduling problems minimising makespan","volume":"240","author":"Vallada","year":"2015","journal-title":"European Journal of Operational Research"},{"key":"10.1016\/j.eswa.2026.133570_b0280","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2025.129536","article-title":"A multi-population co-evolutionary algorithm for solving energy-efficient hybrid flow shop scheduling problem","volume":"297","author":"Wang","year":"2026","journal-title":"Expert Systems with Applications"},{"key":"10.1016\/j.eswa.2026.133570_b0285","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1016\/j.jmsy.2021.08.008","article-title":"A fuzzy hierarchical reinforcement learning based scheduling method for semiconductor wafer manufacturing systems","volume":"61","author":"Wang","year":"2021","journal-title":"Journal of Manufacturing Systems"},{"key":"10.1016\/j.eswa.2026.133570_b0290","doi-asserted-by":"crossref","first-page":"2423","DOI":"10.3390\/pr12112423","article-title":"Dynamic integrated scheduling of production equipment and automated guided vehicles in a flexible job shop based on deep reinforcement learning","volume":"12","author":"Wang","year":"2024","journal-title":"Processes"},{"key":"10.1016\/j.eswa.2026.133570_b0295","article-title":"A knowledge-driven cooperative coevolutionary algorithm for integrated distributed production and transportation scheduling problem","volume":"1\u201314","author":"Wang","year":"2024","journal-title":"IEEE Transactions on Automation Science and Engineering"},{"key":"10.1016\/j.eswa.2026.133570_b0300","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1007\/s11128-021-03384-7","article-title":"Quantum k-means algorithm based on Manhattan distance","volume":"21","author":"Wu","year":"2022","journal-title":"Quantum Information Processing"},{"key":"10.1016\/j.eswa.2026.133570_b0305","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2023.120402","article-title":"A decomposition-based multi-objective Jaya algorithm for lot-streaming job shop scheduling with variable sublots and intermingling setting","volume":"228","author":"Xie","year":"2023","journal-title":"Expert Systems with Applications"},{"key":"10.1016\/j.eswa.2026.133570_b0310","doi-asserted-by":"crossref","first-page":"334","DOI":"10.1016\/j.jmsy.2024.02.007","article-title":"Hybrid quantum particle swarm optimization and variable neighborhood search for flexible job-shop scheduling problem","volume":"73","author":"Xu","year":"2024","journal-title":"Journal of Manufacturing Systems"},{"key":"10.1016\/j.eswa.2026.133570_b0315","doi-asserted-by":"crossref","first-page":"2378","DOI":"10.1109\/TASE.2025.3650678","article-title":"Constraint programming for AGV and machine integrated scheduling problem in flexible manufacturing system","volume":"23","author":"Yao","year":"2026","journal-title":"IEEE Transactions on Automation Science and Engineering"},{"key":"10.1016\/j.eswa.2026.133570_b0320","doi-asserted-by":"crossref","DOI":"10.1016\/j.swevo.2025.102076","article-title":"Multi-objective energy-efficient scheduling of distributed heterogeneous hybrid flow shops via multi-agent double deep Q-Network","volume":"98","author":"Yuan","year":"2025","journal-title":"Swarm and Evolutionary Computation"},{"key":"10.1016\/j.eswa.2026.133570_b0325","doi-asserted-by":"crossref","first-page":"509","DOI":"10.1007\/s10845-023-02252-8","article-title":"Research on flexible job shop scheduling problem with AGV using double DQN","volume":"36","author":"Yuan","year":"2025","journal-title":"Journal of Intelligent Manufacturing"},{"key":"10.1016\/j.eswa.2026.133570_b0330","doi-asserted-by":"crossref","first-page":"2781","DOI":"10.1007\/s40747-023-01288-w","article-title":"Automatic algorithm design of distributed hybrid flowshop scheduling with consistent sublots","volume":"10","author":"Zhang","year":"2024","journal-title":"Complex & Intelligent Systems"},{"key":"10.1016\/j.eswa.2026.133570_b0335","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2021.107305","article-title":"A collaborative variable neighborhood descent algorithm for the hybrid flowshop scheduling problem with consistent sublots","volume":"106","author":"Zhang","year":"2021","journal-title":"Applied Soft Computing"},{"key":"10.1016\/j.eswa.2026.133570_b0340","doi-asserted-by":"crossref","first-page":"441","DOI":"10.1016\/j.ejor.2019.11.016","article-title":"Multi-objective optimisation in flexible assembly job shop scheduling using a distributed ant colony system","volume":"283","author":"Zhang","year":"2020","journal-title":"European Journal of Operational Research"},{"key":"10.1016\/j.eswa.2026.133570_b0345","article-title":"A matheuristic for lot-streaming scheduling in a flexible job shop with variable sublots and intermingling settings","volume":"1\u201330","author":"Zhao","year":"2025","journal-title":"International Journal of Production Research"},{"key":"10.1016\/j.eswa.2026.133570_b0350","doi-asserted-by":"crossref","unstructured":"Zhou, F.-S., Hu, R., Qian, B., Han, S., Yang, Y., Yang, J.-B. (2025). Spatial decomposition-based iterative greedy algorithm for the multi-resource constrained re-entrant hybrid flow shop scheduling problem in semiconductor wafer fabrication. https:\/\/doi.org\/10.2139\/ssrn.4994727.","DOI":"10.2139\/ssrn.4994727"},{"key":"10.1016\/j.eswa.2026.133570_b0355","doi-asserted-by":"crossref","DOI":"10.1016\/j.cor.2026.107388","article-title":"Spatial decomposition-based variable neighborhood search algorithm for the integrated semiconductor backend production and distribution scheduling problem","volume":"189","author":"Zhou","year":"2026","journal-title":"Computers and Operations Research"}],"container-title":["Expert Systems with Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0957417426024796?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0957417426024796?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T23:26:57Z","timestamp":1791934017000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0957417426024796"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2027,1]]},"references-count":71,"alternative-id":["S0957417426024796"],"URL":"https:\/\/doi.org\/10.1016\/j.eswa.2026.133570","relation":{},"ISSN":["0957-4174"],"issn-type":[{"value":"0957-4174","type":"print"}],"subject":[],"published":{"date-parts":[[2027,1]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Deep reinforcement learning\u2013driven space decomposition variable neighborhood search algorithm for distributed heterogeneous factory lot-sizing and scheduling problem","name":"articletitle","label":"Article Title"},{"value":"Expert Systems with Applications","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.eswa.2026.133570","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"133570"}}