nahavandi-applicationofareinforcement-2002.pdf (1.2 MB)
The application of a reinforcement learning agent to a multi-product manufacturing facility
conference contribution
posted on 2002-01-01, 00:00 authored by Douglas CreightonDouglas Creighton, Saeid NahavandiAn 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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Title of proceedings
IEEE ICIT' 02 : 2002 IEEE International Conference on Industrial Technology : productivity reincarnation through robotics & automation : 11-14 December 2002, Shangri-La Hotel, Bangkok, ThailandEvent
IEEE International Conference on Industrial Technology (2002 : Bangkok, Thailand)Pagination
1229 - 1234Publisher
IEEE XploreLocation
Bangkok, ThailandPlace of publication
Piscataway, N.J.Start date
2002-12-11End date
2002-12-14ISBN-13
9780780376571ISBN-10
0780376579Language
engNotes
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E1 Full written paper - refereedCopyright notice
2002, IEEEEditor/Contributor(s)
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