A reinforcement learning approach for the flexible job shop scheduling problem

Authors:
Yailen Martínez;Ann Nowé;Juliett Suárez;Rafael Bello
Affiliations:
CoMo Lab, Department of Computer Science, Vrije Universiteit Brussel, Belgium;CoMo Lab, Department of Computer Science, Vrije Universiteit Brussel, Belgium;Department of Computer Science, Central University of Las Villas, Cuba;Department of Computer Science, Central University of Las Villas, Cuba
Venue:
LION'05 Proceedings of the 5th international conference on Learning and Intelligent Optimization
Year:
2011

Citing 6
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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.