Double deep Q-network-based self-adaptive scheduling approach for smart shop floor
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
https://link.springer.com/content/pdf/10.1007/s00521-023-08877-3.pdf
Reference41 articles.
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2. Tao F, Qing QL, Liu A, Kusiak A (2018) Data-driven smart manufacturing. J Manuf Syst 48:157–169. https://doi.org/10.1016/j.jmsy.2018.01.006
3. Zhang YF, Wang J, Liu SC, Qian C (2017) Game theory based real-time shop floor scheduling strategy and method for cloud manufacturing. Int J Intell Syst 32(4):437–463. https://doi.org/10.1002/int.21868
4. Zhang GH, Lu XX, Liu X, Zhang LT, Wei SW, Wang WQ (2022) An effective two-stage algorithm based on convolutional neural network for the bi-objective flexible job shop scheduling problem with machine breakdown. Expert Syst Appl 203:117460. https://doi.org/10.1016/j.eswa.2022.117460
5. Wang JL, Gao PJ, Zhang P, Zhang J, Ip WH (2021) A fuzzy hierarchical reinforcement learning based scheduling method for semiconductor wafer manufacturing systems. J Manuf Syst 61:239–248. https://doi.org/10.1016/j.jmsy.2021.08.008
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