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A Reinforcement Learning Approach for the Flexible Job Shop Scheduling Problem Host Publication: Proc. Fifth International Conference on Learning and Intelligent Optimization (LION5) Authors: Y. Martinez Jimenez, A. Nowé, S. Juliett and B. Rafael Publisher: Lecture Notes in Computer Science, Springer Publication Year: 2011 Number of Pages: 10 ISBN: 978-3-642-25565-6
Abstract: In this work we present a Reinforcement Learning approach for the Flexible Job Shop Scheduling problem. The proposed approach
follows the ideas of the hierarchical approaches and combines learning and optimization in order to achieve better results. Several problem instances were used to test the algorithm and to compare the results with those reported by previous approaches.
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