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Measuring the network robustness by Monte Carlo estimation of shortest path length distribution

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  • Morohosi, Hozumi

Abstract

Two kinds of robustness measure for networks are introduced and applied to the road network systems in Japan. One is on the connectivity of randomly chosen pair of vertices, another is on the shortest path length between pair of connected vertices. We devise Monte Carlo methods for the computation of two measures.

Suggested Citation

  • Morohosi, Hozumi, 2010. "Measuring the network robustness by Monte Carlo estimation of shortest path length distribution," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(3), pages 551-559.
    • Handle: RePEc:eee:matcom:v:81:y:2010:i:3:p:551-559
    DOI: 10.1016/j.matcom.2010.07.022
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    Cited by:

    1. Yaoming Zhou & Jiuh‐Biing Sheu & Junwei Wang, 2017. "Robustness Assessment of Urban Road Network with Consideration of Multiple Hazard Events," Risk Analysis, John Wiley & Sons, vol. 37(8), pages 1477-1494, August.
    2. Oliveira, J.G. & Dorogovtsev, S.N. & Mendes, J.F.F., 2023. "Statistics of remote regions of networks," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
    3. Vodák, Rostislav & Bíl, Michal & Sedoník, Jiří, 2015. "Network robustness and random processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 368-382.

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