Estimation of reliability and its derivatives for large time horizons in Markovian systems

Perwez Shahabuddin, Marvin Nakayama

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

Abstract

A number of importance sampling methods have been previously proposed for estimating the system unreliability of highly reliable Markovian systems. These techniques are effective when the time horizon of interest is small. However, for large time horizons, these methods are no longer efficient. We describe a technique in which instead of estimating the actual measure, we estimate bounds on the measure. The bounds can be estimated efficiently, and for large time horizons, they are close to the actual measure. Similar techniques for derivative estimation are also presented.

Original languageEnglish (US)
Title of host publicationWinter Simulation Conference Proceedings
EditorsGerald W. Evans, Mansooren Mollaghasemi, Edward C. Russell, William E. Biles
PublisherPubl by IEEE
Pages422-429
Number of pages8
ISBN (Print)0780313801
StatePublished - Dec 1 1993
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Chemical Health and Safety
  • Software
  • Safety, Risk, Reliability and Quality
  • Applied Mathematics
  • Modeling and Simulation

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