Reentrant hybrid flow shop scheduling with stockers in automated material handling systems using deep reinforcement learning

Author:

Lin Chun-ChengORCID,Peng Yi-Chun,Chang Yung-Sheng,Chang Chun-Hsiang

Funder

National Science and Technology Council

Publisher

Elsevier BV

Reference39 articles.

1. Bi-objective scheduling for reentrant hybrid flow shop using pareto genetic algorithm;Cho;Computers & Industrial Engineering,2011

2. A two-level method of production planning and scheduling for bi-objective reentrant hybrid flow shops;Cho;Computers & Industrial Engineering,2017

3. Du, Y., Li, J., Li, C., & Duan, P. (in press). A reinforcement learning approach for flexible job shop scheduling problem with crane transportation and setup times.IEEE Transactions on Neural Networks and Learning Systems 2022.

4. New multi-objective method to solve reentrant hybrid flow shop scheduling problem;Dugardin;European Journal of Operational Research,2010

5. Emmons, H., & Vairaktarakis, G. (2012). Flow shop scheduling: theoretical results, algorithms, and applications. In vol. 182 of International Series in Operations Research & Management Science, New York: Springer.

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