A Deep-Reinforcement-Learning-Based Optimization Approach for Real-Time Scheduling in Cloud Manufacturing

A Deep-Reinforcement-Learning-Based Optimization Approach for Real-Time Scheduling in Cloud Manufacturing

Resource scheduling problems (RSPs) in cloud manufacturing (CMfg) often manifest as dynamic scheduling problems in which scheduling strategies depend on real-time environments and demands. Generally, multiple resources in the CMfg scheduling process cause difficulties in system modeling. To solve th...

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Bibliographic Details
Main Authors: Huayu Zhu, Mengrong Li, Yong Tang, Yanfei Sun
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Cloud manufacturing
deep reinforcement learning
real-time
dynamic data
resource scheduling
optimization
Online Access:https://ieeexplore.ieee.org/document/8952684/

Internet

https://ieeexplore.ieee.org/document/8952684/

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