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

V. G. Kulkarni and J. S. Provan
Additional contact information
V. G. Kulkarni: University of North Carolina, Chapel Hill, North Carolina
J. S. Provan: University of North Carolina, Chapel Hill, North Carolina

Operations Research, 1985, vol. 33, issue 6, 1389-1393

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.

Keywords: 483 distribution of shortest path lengths; 488 path lengths in stochastic networks; 769 efficient Monte Carlo implementation (search for similar items in EconPapers)
Date: 1985
References: Add references at CitEc
Citations:

Downloads: (external link)
http://dx.doi.org/10.1287/opre.33.6.1389 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:oropre:v:33:y:1985:i:6:p:1389-1393

Access Statistics for this article

More articles in Operations Research from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().