Deep Reinforcement Learning Algorithm for Permutation Flow Shop Scheduling Problem
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-13832-4_39
Reference26 articles.
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3. Neufeld, J.S., Gupta, J.N.D., Buscher, U.: A comprehensive review of flowshop group scheduling literature. Comput. Oper. Res. 70(1), 56–74 (2016)
4. Fernandez-Viagas, V., Ruiz, R., Framinan, J.M.: A new vision of approximate methods for the permutation flowshop to minimise makespan: state-of-the-art and computational evaluation. Eur. J. Oper. Res. 257(3), 707–721 (2017)
5. Mahmoudi, M., Zhou, X.S.: Finding optimal solutions for vehicle routing problem with pickup and delivery services with time windows: a dynamic programming approach based on state-space-time network representations. Transp. Res. Part B 89, 19–42 (2016)
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