In the present work, cellular automata are combined with Monte Carlo sampling to solve two critical problems related to the unreliability assessment of complex networks composed of nodes interconnected by binary arcs: the identification of the minimal cut sets of the network and the computation of the Fussell—Vesely importance measures assessing the criticality of each arc with respect to the network unreliability. The effectiveness of the method is tested on two literature case studies.
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