Flexible Job-Shop Scheduling via Graph Neural Network and Deep Reinforcement Learning
Author:
Affiliation:
1. Institute of Marine Science and Technology, Shandong University, Qingdao, China
2. School of Control Science and Engineering, Shandong University, Jinan, China
3. Singapore Institute of Manufacturing Technology, Singapore
Funder
National Natural Science Foundation of China
Natural Science Foundation of Shandong Province
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Computer Science Applications,Information Systems,Control and Systems Engineering
Link
http://xplorestaging.ieee.org/ielx7/9424/9989328/09826438.pdf?arnumber=9826438
Reference46 articles.
1. Graph attention networks;veli?kovi?;Proc Int Conf Learn Representations,0
2. Heterogeneous Graph Neural Network via Attribute Completion
3. Dynamic multi-objective scheduling for flexible job shop by deep reinforcement learning
4. A Comprehensive Survey on Graph Neural Networks
5. Deep Reinforcement Learning Based Optimization Algorithm for Permutation Flow-Shop Scheduling
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