Expert-Guided Deep Reinforcement Learning for Flexible Job Shop Scheduling Problem
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-2275-4_4
Reference18 articles.
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3. Chen, R., Yang, B., Li, S., Wang, S.: A self-learning genetic algorithm based on reinforcement learning for flexible job-shop scheduling problem. Comput. Industr. Eng. 149, 106778 (2020)
4. Gabel, T., Riedmiller, M.: Distributed policy search reinforcement learning for job-shop scheduling tasks. Int. J. Prod. Res. 50(1), 41–61 (2012)
5. Gao, K.Z., Suganthan, P.N., Chua, T.J., Chong, C.S., Cai, T.X., Pan, Q.K.: A two-stage artificial bee colony algorithm scheduling flexible job-shop scheduling problem with new job insertion. Expert Syst. Appl. 42(21), 7652–7663 (2015)
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