The application of a reinforcement learning agent to a multi-product manufacturing facility
Creighton, Douglas and Nahavandi, Saeid 2002, The application of a reinforcement learning agent to a multi-product manufacturing facility, in IEEE ICIT' 02 : 2002 IEEE International Conference on Industrial Technology : productivity reincarnation through robotics & automation : 11-14 December 2002, Shangri-La Hotel, Bangkok, Thailand, IEEE Xplore, Piscataway, N.J., pp. 1229-1234.
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An intelligent agent-based scheduling system, consisting of a reinforcement learning agent and a simulation model has been developed and tested on a classic scheduling problem. The production facility studied is a multiproduct serial line subject to stochastic failure. The agent goal is to minimise total production costs, through selection of job sequence and batch size. To explore state space the agent used reinforcement learning. By applying an independent inventory control policy for each product, the agent successfully identified optimal operating policies for a real production facility.
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