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We present and compare two different approaches for the transient solution of Markov regenerative stochastic Petri Nets: the method based on Markov regenerative theory and the method of supplementary variables. In both cases the equations that govern the marking process of the non-Markovian stochastic Petri net are presented and then solved either in time-domain or using a Laplace-Stieltjes transformation. Then a comparison of both approaches is presented: expressions for asymptotic computational costs and storage requirements are developed and experimental studies are performed to compare accuracy, time, and space complexity.