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Reinforcement learning approach to re-entrant manufacturing system scheduling

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4 Author(s)
Chang-chun Liu ; Shenyang Inst. of Autom., Chinese Acad. of Sci., Shenyang, China ; Hui-yu Jin ; Yu Tian ; Hai-Bin Yu

In this paper, we focus on the problem of optimally scheduling a closed re-entrant system with one type of parts and two service centers, each of which consisting of one machine. An algorithm based on reinforcement learning is proposed. The results of the experiments indicate that reinforcement learning can outperform some familiar heuristic methods and is closed to the workload balancing policy

Published in:

Info-tech and Info-net, 2001. Proceedings. ICII 2001 - Beijing. 2001 International Conferences on  (Volume:3 )

Date of Conference:

2001