Journal
RELIABILITY ENGINEERING & SYSTEM SAFETY
Volume 83, Issue 3, Pages 277-286Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.ress.2003.09.021
Keywords
Bayes point estimators; confidence degree; fuzzy real numbers; nonlinear programming; system reliability
Ask authors/readers for more resources
The Bayesian system reliability assessment under fuzzy environments is proposed in this paper. In order to apply the Bayesian approach, the fuzzy parameters are assumed as fuzzy random variables with fuzzy prior distributions. The (conventional) Bayes estimation method will be used to create the fuzzy Bayes point estimator of system reliability by invoking the well-known theorem called 'Resolution Identity' in fuzzy sets theory. On the other hand, we also provide the computational procedures to evaluate the membership degree of any given Bayes point estimate of system reliability. In order to achieve this purpose, we transform the original problem into a nonlinear programming problem. This nonlinear programming problem is then divided into four subproblems for the purpose of simplifying computation. Finally, the subproblems can be solved by using any commercial optimizers, e.g. GAMS or LINGO. (C) 2003 Elsevier Ltd. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available