https://orcid.org/0000-0003-4099-0179
Citations (70)
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Xiaohan Wang, Lin Zhang, Yongkui Liu & Yuanjun Laili. (2024) An improved deep reinforcement learning-based scheduling approach for dynamic task scheduling in cloud manufacturing. International Journal of Production Research 62:11, pages 4014-4030.
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Likun Wang, Zi Wang, Peter Kendall, Kevin Gumma, Alison Turner & Svetan Ratchev. (2024) Digital-twin deep dynamic camera position optimisation for the V-STARS photogrammetry system based on 3D reconstruction. International Journal of Production Research 62:11, pages 3932-3951.
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Fatima Ezzahra Achamrah & Ali Attajer. (2024) Multi-objective reinforcement learning-based framework for solving selective maintenance problems in reconfigurable cyber-physical manufacturing systems. International Journal of Production Research 62:10, pages 3460-3482.
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Marcel Panzer, Benedict Bender & Norbert Gronau. (2024) A deep reinforcement learning based hyper-heuristic for modular production control. International Journal of Production Research 62:8, pages 2747-2768.
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Xinyue Wang, Tao Ren, Danyu Bai, Feng Chu, Yaodong Yu, Fanchun Meng & Chin-Chia Wu. (2024) Scheduling a multi-agent flow shop with two scenarios and release dates. International Journal of Production Research 62:1-2, pages 421-443.
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Hanting Zhou, Wenhe Chen, Changqing Shen, Longsheng Cheng & Min Xia. (2023) Intelligent machine fault diagnosis with effective denoising using EEMD-ICA- FuzzyEn and CNN. International Journal of Production Research 61:23, pages 8252-8264.
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Huosong Xia, Yuan Wang, Sajjad Jasimuddin, Justin Zuopeng Zhang & Andrew Thomas. (2023) A big-data-driven matching model based on deep reinforcement learning for cotton blending. International Journal of Production Research 61:22, pages 7573-7591.
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Victor Delpla, Kevin Chapron, Jean-Pierre Kenné & Lucas A. Hof. (2023) A novel approach for predicting Lockout/Tagout safety procedures for smart maintenance strategies. International Journal of Production Research 0:0, pages 1-22.
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Henry C. Croll, Kaoru Ikuma, Say Kee Ong & Soumik Sarkar. (2023) Reinforcement learning applied to wastewater treatment process control optimization: Approaches, challenges, and path forward. Critical Reviews in Environmental Science and Technology 53:20, pages 1775-1794.
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Ana Esteso, David Peidro, Josefa Mula & Manuel Díaz-Madroñero. (2023) Reinforcement learning applied to production planning and control. International Journal of Production Research 61:16, pages 5772-5789.
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Changqing Liu, Yingguang Li, Chong Huang, Yujie Zhao & Zhiwei Zhao. (2023) A meta-reinforcement learning method by incorporating simulation and real data for machining deformation control of finishing process. International Journal of Production Research 61:4, pages 1114-1128.
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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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Lin Gong, Zijie Huang, Xi Xiang & Xin Liu. Real-time AGV scheduling optimisation method with deep reinforcement learning for energy-efficiency in the container terminal yard. International Journal of Production Research 0:0, pages 1-21.
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Zhenrui Ji, Gang Liu, Wenjun Xu, Bitao Yao, Xuedong Liu & Zude Zhou. Deep reinforcement learning on variable stiffness compliant control for programming-free robotic assembly in smart manufacturing. International Journal of Production Research 0:0, pages 1-23.
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Xiaoyan Zhou & Ian Flood. (2024) Optimization and evaluation of a neural network based policy for real-time control of construction factory processes. Journal of Information Technology in Construction 29, pages 84-98.
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Eungjin Kim, Taehyung Kim, Dongcheol Lee, Hyeongook Kim, Sehwan Kim, Jaewon Kim, Woosub Kim, Eunzi Kim, Younggil Jin & Tae-Eog Lee. (2024) Practical Reinforcement Learning for Adaptive Photolithography Scheduler in Mass Production. IEEE Transactions on Semiconductor Manufacturing 37:1, pages 16-26.
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Xu Zheng & Zhen Chen. (2024) An improved deep Q-learning algorithm for a trade-off between energy consumption and productivity in batch scheduling. Computers & Industrial Engineering 188, pages 109925.
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Yaping Zhao, Siqi Ma, Xiangzhi Mo & Xiaoyun Xu. (2024) Data-driven optimization for energy-constrained dietary supplement scheduling: A bounded cut MP-DQN approach. Computers & Industrial Engineering 188, pages 109894.
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András Rácz-Szabó, Tamás Ruppert & János Abonyi. (2024) Enhancing material supply for an automated production line by implementing a Markov Decision Process model for AGV-based material handling. Enhancing material supply for an automated production line by implementing a Markov Decision Process model for AGV-based material handling.
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Smita Abhijit Ganjare, Sunil M. Satao & Vaibhav Narwane. (2023) Systematic literature review of machine learning for manufacturing supply chain. The TQM Journal.
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Zhewei Liu & Dayong Guo. (2023) Assessing the carbon footprint of soccer events through a lightweight CNN model utilizing transfer learning in the pursuit of carbon neutrality. Frontiers in Ecology and Evolution 11.
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Cong Zhang, Yaoxin Wu, Yining Ma, Wen Song, Zhang Le, Zhiguang Cao & Jie Zhang. (2023) A review on learning to solve combinatorial optimisation problems in manufacturing. IET Collaborative Intelligent Manufacturing 5:1.
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