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A Reinforcement Learning Approach for theFlexible Job Shop Scheduling Problem

机译:一种强化学习方法,可靠的职位店调度问题

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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 in-stances were used to test the algorithm and to compare the results with those reported by previous approaches.
机译:在这项工作中,我们为灵活的作业商店调度问题提出了一种强化学习方法。所提出的方法遵循分层方法的思想,并结合学习和优化,以实现更好的结果。使用若干问题用于测试算法,并将结果与​​先前方法报告的结果进行比较。

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