Abstract
The paper investigates a stochastic production scheduling problem with unrelated parallel machines. A closed-loop scheduling technique is presented that on-line controls the production process. To achieve this, the scheduling problem is reformulated as a special Markov Decision Process. A near-optimal control policy of the resulted MDP is calculated in a homogeneous multi-agent system. Each agent applies a trial-based approximate dynamic programming method. Different cooperation techniques to distribute the value function computation among the agents are described. Finally, some benchmark experimental results are shown.
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Csáji, B.C., Monostori, L. (2005). Stochastic Reactive Production Scheduling by Multi-agent Based Asynchronous Approximate Dynamic Programming. In: Pěchouček, M., Petta, P., Varga, L.Z. (eds) Multi-Agent Systems and Applications IV. CEEMAS 2005. Lecture Notes in Computer Science(), vol 3690. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11559221_39
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DOI: https://doi.org/10.1007/11559221_39
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29046-9
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