Abstract
This paper deals with stochastic activity networks with independent and continuously distributed activity durations. We show that such stochastic networks can be modeled as continuous-time Markov processes with a single absorbing state using a supplementary variable technique. The following quantities are obtained: (i) the probability distribution of the project completion time (longest path), (ii) the probability distribution of the shortest path length.
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