In: IEEE Computer Soc. Press, Proc. of 6th International Workshop on Petri Nets and Performance Models - PNPM'95, Durham, N. Carolina, USA, pages 252-260. 1995.
Abstract: The paper presents an approach to formalize decomposition and aggregation of stochastic reward nets based on their structure. The sets of places and transitions are automatically partitioned. Stets of these partitions are aggregated. Partial and full aggregates are built for an iterative scheme to calculate approximately stochastic rewards. In order words, approximate performance evaluation is fully automated for any live, bounded and reversible stochastic reward net, as far as at least one aggregable partition is found. The technique is applied to the analysis of a flexible manufacturing system.