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Technical Note—An Improved Implementation of Conditional Monte Carlo Estimation of Path Lengths in Stochastic Networks

Author

Listed:
  • V. G. Kulkarni

    (University of North Carolina, Chapel Hill, North Carolina)

  • J. S. Provan

    (University of North Carolina, Chapel Hill, North Carolina)

Abstract

This note suggests an improvement to the Monte Carlo simulation technique of Sigal, Pritsker and Solberg for estimating the distribution of the shortest/longest path length in a stochastic network. This improvement also applies in network reliability estimation and PERT analysis.

Suggested Citation

  • V. G. Kulkarni & J. S. Provan, 1985. "Technical Note—An Improved Implementation of Conditional Monte Carlo Estimation of Path Lengths in Stochastic Networks," Operations Research, INFORMS, vol. 33(6), pages 1389-1393, December.
    • Handle: RePEc:inm:oropre:v:33:y:1985:i:6:p:1389-1393
    DOI: 10.1287/opre.33.6.1389
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