Abstract
This paper deals with a real-time scheduling system of the Holonic Manufacturing Systems (HMSs). In the previous papers, real-time scheduling method based on the utility values have been proposed and applied to the HMSs. In this method, individual job holons and resource holons determine the utility values for the next machining operation based on their own decision criteria. Reinforcement learning is applied to the job holons, in the paper, in order to make the suitable decision criteria for determination of utility values. Some case studies of the real-time scheduling are carried out to verify the effectiveness of the proposed method.
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