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A new simulation method based on the RVR principle for the rare event network reliability problem

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  • H. Cancela
  • M. Khadiri
  • G. Rubino

Abstract

In this paper we consider the evaluation of the well known [InlineEquation not available: see fulltext.]-network unreliability parameter by means of a new RVR Monte-Carlo method. This method is based on series-parallel reductions and a partitioning procedure using pathsets and cutsets for recursively changing the original problem into similar ones on smaller networks. By means of several experimental results, we show that the proposed method has good performances in rare event cases and offers significant gains over other state-of-the-art variance reduction techniques. Copyright Springer Science+Business Media, LLC 2012

Suggested Citation

  • H. Cancela & M. Khadiri & G. Rubino, 2012. "A new simulation method based on the RVR principle for the rare event network reliability problem," Annals of Operations Research, Springer, vol. 196(1), pages 111-136, July.
    • Handle: RePEc:spr:annopr:v:196:y:2012:i:1:p:111-136:10.1007/s10479-011-1017-x
    DOI: 10.1007/s10479-011-1017-x
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    References listed on IDEAS

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    1. K.-P. Hui & N. Bean & M. Kraetzl & Dirk Kroese, 2005. "The Cross-Entropy Method for Network Reliability Estimation," Annals of Operations Research, Springer, vol. 134(1), pages 101-118, February.
    2. Sheldon M. Ross, 1994. "A new simulation estimator of system reliability," International Journal of Stochastic Analysis, Hindawi, vol. 7, pages 1-6, January.
    3. George S. Fishman, 1986. "A Monte Carlo Sampling Plan for Estimating Network Reliability," Operations Research, INFORMS, vol. 34(4), pages 581-594, August.
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    Cited by:

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    2. Lirong Cui & Shijia Du & Aofu Zhang, 2014. "Reliability measures for two-part partition of states for aggregated Markov repairable systems," Annals of Operations Research, Springer, vol. 212(1), pages 93-114, January.

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