Using real-time manufacturing data to schedule a smart factory via reinforcement learning
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- @Article{GU:2022:cie,
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author = "Wenbin Gu and Yuxin Li and Dunbing Tang and
Xianliang Wang and Minghai Yuan",
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title = "Using real-time manufacturing data to schedule a smart
factory via reinforcement learning",
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journal = "Computer \& Industrial Engineering",
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volume = "171",
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pages = "108406",
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year = "2022",
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ISSN = "0360-8352",
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DOI = "doi:10.1016/j.cie.2022.108406",
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URL = "https://www.sciencedirect.com/science/article/pii/S0360835222004466",
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keywords = "genetic algorithms, genetic programming, Smart
factory, Real-time scheduling, Production state
clustering, Reinforcement learning",
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abstract = "Under the background of intelligent manufacturing,
internet of things and other information technologies
have accumulated a large amount of data for
manufacturing system. However, the traditional
scheduling methods often ignore the production law and
knowledge hidden in the manufacturing data. Therefore,
this paper proposes a cyber-physical architecture and a
communication protocol for smart factory, and a
multiagent-system-based dynamic scheduling mechanism is
given using contract net protocol. In the dynamic
scheduling mechanism, the problem formulation module
and scheduling point module are designed first. Then, a
genetic programming (GP) method is proposed to form
sixteen high-quality rules, which constitute the
scheduling rule library. Meanwhile, combining with
autoencoder, self-organizing mapping neural network and
k-means clustering algorithm, the state clustering
module is designed to realize the efficient clustering
of production attribute vector. Moreover, an improved
Q-learning algorithm is used to train the GP rule
selector, so that the decision-making agent can choose
the appropriate GP rule according to the production
state at each scheduling point. Finally, the
experimental results show that the proposed method has
feasibility and superiority compared with other methods
in real-time scheduling, and can effectively deal with
disturbance events in the manufacturing process",
- }
Genetic Programming entries for
Wenbin Gu
Yuxin Li
Dunbing Tang
Xianliang Wang
Minghai Yuan
Citations