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International Journal of Production Research Volume 59, 2021 - Issue 19
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Adaptive scheduling for assembly job shop with uncertain assembly times based on dual Q-learning

Haoxiang Wanga College of Engineering, Nanjing Agricultural University, Nanjing, People’s Republic of ChinaView further author information
,
Bhaba R. Sarkerb Department of Mechanical & Industrial Engineering, Louisiana State University, Baton Rouge, LA, USACorrespondence[email protected]
View further author information
,
Jing Lia College of Engineering, Nanjing Agricultural University, Nanjing, People’s Republic of ChinaView further author information
&
Jian Lia College of Engineering, Nanjing Agricultural University, Nanjing, People’s Republic of ChinaView further author information
Pages 5867-5883 | Received 25 Jun 2019, Accepted 02 Jul 2020, Published online: 29 Jul 2020

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Yuting Wu, Ling Wang, Jing-fang Chen, Jie Zheng & Zixiao Pan. (2024) A reinforcement learning driven two-stage evolutionary optimisation for hybrid seru system scheduling with worker transfer. International Journal of Production Research 62:11, pages 3952-3971.
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Marzieh Khakifirooz, Michel Fathi, Alexandre Dolgui & Panos M. Pardalos. (2024) Scheduling in Industrial environment toward future: insights from Jean-Marie Proth. International Journal of Production Research 62:1-2, pages 291-317.
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Omar Abbaas & Jose A. Ventura. (2023) A multi-agent resource bidding algorithm for order acceptance and assembly job shop scheduling. International Journal of Production Research 0:0, pages 1-28.
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Abebaw Degu Workneh & Maha Gmira. (2023) Learning to schedule (L2S): adaptive job shop scheduling using double deep Q network. Smart Science 11:3, pages 409-423.
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Renke Liu, Rajesh Piplani & Carlos Toro. (2022) Deep reinforcement learning for dynamic scheduling of a flexible job shop. International Journal of Production Research 60:13, pages 4049-4069.
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Marcel Panzer & Benedict Bender. (2022) Deep reinforcement learning in production systems: a systematic literature review. International Journal of Production Research 60:13, pages 4316-4341.
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Amel Jaoua, Samar Masmoudi & Elisa Negri. Digital twin-based reinforcement learning framework: application to autonomous mobile robot dispatching. International Journal of Computer Integrated Manufacturing 0:0, pages 1-24.
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Sharareh Taghipour, Hamed A. Namoura, Mani Sharifi & Mageed Ghaleb. Real-time production scheduling using a deep reinforcement learning-based multi-agent approach. INFOR: Information Systems and Operational Research 0:0, pages 1-25.
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Shichen Tian, Chunjiang Zhang, Jiaxin Fan, Xinyu Li & Liang Gao. (2024) A genetic algorithm with critical path-based variable neighborhood search for distributed assembly job shop scheduling problem. Swarm and Evolutionary Computation 85, pages 101485.
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