Stochastic Reactive Production Scheduling by Multi-Agent Based Asynchronous Approximate Dynamic Programming

 
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Csáji, Balázs Csanád and Monostori, László (2005) Stochastic Reactive Production Scheduling by Multi-Agent Based Asynchronous Approximate Dynamic Programming. In: Multi-Agent Systems and Applications IV (CEEMAS 2005). Lecture Notes in Artificial Intelligence, 3690. Springer, Germany, pp. 388-397.

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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. Di®erent cooperation techniques to distribute the value function computation among the agents are described. Finally, some benchmark experimental results are shown.

Deposited by Balázs Csanád Csáji on 04 October 2005

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