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System Reliability By Simulation: Random Hazards Versus Importance Sampling

Published online by Cambridge University Press:  27 July 2009

Chi Hyuck Jun  and
Sheldon M. Ross
Chi Hyuck Jun
Affiliation:
Department of Industrial Engineering Pohang Institute of Science and Technology Pohang, Korea
Sheldon M. Ross
Affiliation:
Department of Industrial Engineering and Operations Research University of California, Berkeley, California 94720
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Abstract

Two approaches for simulating the reliability function are considered–one using the total hazard estimator and the other using importance sampling. It is shown both for the Wheatstone Bridge System and for a triangular system that the total hazard estimator has significantly smaller variance when compared both to the standard importance sampling estimator and to an improved version of it.

Type
Articles
Information
Probability in the Engineering and Informational Sciences , Volume 6 , Issue 1 , January 1992 , pp. 119 - 126
Copyright
Copyright © Cambridge University Press 1992

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References

Keilson, J. (1979). Markov chain models–Rarity and exponentiality. New York: Springer.CrossRefGoogle Scholar
Kijima, M. (1987). Some results for uniformizable semi-Markov processes. Australian Journal of Statistics 29: 193–207.CrossRefGoogle Scholar
Kijima, M. (1989). Upper bounds of a measure of dependence and the relaxation time for finite Markov chains. Journal of Operations Research Society of Japan 32: 93–102.CrossRefGoogle Scholar
Ross, S.M. (1987). Approximating transition probabilities and mean occupation times in continuous-time Markov chains. Probability in the Engineering and Informational Sciences 1: 251–264.CrossRefGoogle Scholar
Stoyan, D. (1983). Comparison methods for queues and other stochastic models. New York: Wiley.Google Scholar
Sumita, U. & Shanthikumar, J.G. (1986). A software reliability model with multiple-error introduction and removal. IEEE Transactions on Reliability R-35: 459–462.Google Scholar
Yoon, B.S. & Shanthikumar, J.G. (1989). Bounds and approximations for the transient behavior of continuous-time Markov chains. Probability in the Engineering and Informational Sciences 3: 175–198.CrossRefGoogle Scholar