A decomposition approach for stochastic reward net models

Gianfranco Ciardo, Kishor S. Trivedi
1993 Performance evaluation (Print)  
We present a decomposition approach for the solution of large stochastic reward nets (SRNs) based on the concept of near-independence. The overall model consists of a set of submodels whose interactions are described by an import graph. Each node of the graph corresponds to a parametric SRN submodel and an arc from submodel A to submodel B corresponds to a parameter value that B must receive from A. The quantities exchanged between submodels are based on only three primitives. The import graph
more » ... ormally contains cycles, so the solution method is based on fixed point iteration. Any SRN containing one or more of the nearly-independent structures we present, commonly encountered in practice, can be analyzed using our approach. No other restriction on the SRN is required. We apply our technique to the analysis of a flexible manufacturing system. Short Title: A Decomposition Approach for Stochastic Reward Net Models.
doi:10.1016/0166-5316(93)90026-q fatcat:do5rblpldbaltmd6rtvuoqevrq