Abstract
An algorithm for exact parametric analysis of stochastic Petri nets is presented. The algorithm is derived from the theory of decomposition and aggregation of Markov chains. The transition rate of interest is confined into a diagonal submatrix of the associated Markov chain by row and column permutations. Every time a new value is assigned to the transition, a smaller Markov chain is analyzed. As a result, the computational cost is greatly reduced. >
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