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A combined Monte Carlo and cellular automata approach to the unreliability analysis of binary network systems

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  • E Zio
  • M Librizzi
  • G Sansavini

Abstract

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.

Suggested Citation

  • E Zio & M Librizzi & G Sansavini, 2008. "A combined Monte Carlo and cellular automata approach to the unreliability analysis of binary network systems," Journal of Risk and Reliability, , vol. 222(1), pages 31-38, March.
    • Handle: RePEc:sae:risrel:v:222:y:2008:i:1:p:31-38
    DOI: 10.1243/1748006XJRR66
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    References listed on IDEAS

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    1. Podofillini, Luca & Zio, Enrico & Vatn, Jørn, 2006. "Risk-informed optimisation of railway tracks inspection and maintenance procedures," Reliability Engineering and System Safety, Elsevier, vol. 91(1), pages 20-35.
    2. Zio, Enrico & Podofillini, Luca & Zille, Valérie, 2006. "A combination of Monte Carlo simulation and cellular automata for computing the availability of complex network systems," Reliability Engineering and System Safety, Elsevier, vol. 91(2), pages 181-190.
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    Cited by:

    1. Zio, E. & Golea, L.R., 2012. "Analyzing the topological, electrical and reliability characteristics of a power transmission system for identifying its critical elements," Reliability Engineering and System Safety, Elsevier, vol. 101(C), pages 67-74.

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