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A decomposition approach for stochastic reward net models
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
doi:10.1016/0166-5316(93)90026-q
fatcat:do5rblpldbaltmd6rtvuoqevrq