Variance reduction in mean time to failure simulations

Authors:
Perwez Shahabuddin;Victor F. Nicola;Philip Heidelberger;Ambuj Goyal;Peter W. Glynn
Affiliations:
Department of Operations Research, Stanford University, Stanford, California;IBM Research Division, T.J. Watson Research Center, P.O. Box 704, Yorktown Heights, New York;IBM Research Division, T.J. Watson Research Center, P.O. Box 704, Yorktown Heights, New York;IBM Research Division, T.J. Watson Research Center, P.O. Box 704, Yorktown Heights, New York;Department of Operations Research, Stanford University, Stanford, California
Venue:
WSC '88 Proceedings of the 20th conference on Winter simulation
Year:
1988

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Abstract

We describe two variance reduction methods for estimating the mean time to failure (MTTF) in Markovian models of highly reliable systems. The first method is based on a ratio representation of the MTTF and employs importance sampling. The second method is based on a hybrid simulation/analytic technique where the number of simulated transitions are reduced by computing partial results analytically. Experiments with a large example show the effectiveness of both techniques for highly reliable systems.