Logistics-involved service composition in a dynamic cloud manufacturing environment: A DDPG-based approach

•A Deep Deterministic Policy Gradient (DDPG)-based approach to service composition in cloud manufacturing is proposed.•Performance of DDPG is examined in both static and dynamic cloud manufacturing environments.•DDPG is able to effectively coping with cloud manufacturing service composition and outp...

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Vydané v:	Robotics and computer-integrated manufacturing Ročník 76; s. 102323
Hlavní autori:	Liu, Yongkui, Liang, Huagang, Xiao, Yingying, Zhang, Haifeng, Zhang, Jingxin, Zhang, Lin, Wang, Lihui
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Oxford Elsevier Ltd 01.08.2022 Elsevier BV
Predmet:	Algorithms Ant Colony Optimization Cloud manufacturing Composition Convergence deep deterministic policy gradient algorithm deep deterministic policy gradient algorithm, Ant Colony Optimization deep reinforcement learning Heuristic methods Logistics Machine learning Manufacturing service composition Cloud manufacturing deep deterministic policy gradient algorithm, Ant Colony Optimization deep reinforcement learning service composition
ISSN:	0736-5845, 1879-2537, 1879-2537
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