Research on HFS Scheduling Based on D3QN-RepVGG-CBAM Algorithm
Author:
Affiliation:
1. School of Information Engineering, Guangdong University of Technology, China
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3671151.3671278
Reference16 articles.
1. Improved fruit fly optimization algorithm for solving the hybrid flow shop scheduling problem;Yongqiang WANG;Control Theory & Applications,2023
2. Yu Meng Liu Dehan.Improved PSO-GA algorithm to solve the mixed flow shop scheduling problem [J].Journal of Wuhan University of Technology(Transportation Science and Engineering) 2021 45(3):586-590
3. Hybrid Flow-Shop Scheduling (HFS) Problem Solving with Migrating Birds Optimization (MBO) Algorithm
4. A Reinforcement Learning Method for a Hybrid Flow-Shop Scheduling Problem
5. Petri-net-based dynamic scheduling of flexible manufacturing system via deep reinforcement learning with graph convolutional network
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