The balanced likelihood ratio method for estimating performance measures of highly reliable systems

Author

Alexopoulos, Christos ; Shultes, Bruce C.

Author_Institution

Sch. of Ind. & Syst. Eng., Georgia Inst. of Technol., Atlanta, GA, USA

Volume

2

fYear

1998

fDate

13-16 Dec 1998

Firstpage

1479

Abstract

Over the past several years importance sampling in conjunction with regenerative simulation has been presented as a promising method for estimating reliability parameters in highly reliable systems. Existing methods fail to provide benefits over crude Monte Carlo for the analysis of systems that contain significant component redundancies. The paper presents refined importance sampling techniques along with a generalized regenerative model. The proposed methods have solid theoretical properties and work well in practice

Keywords

digital simulation; importance sampling; redundancy; reliability; Monte Carlo; balanced likelihood ratio method; component redundancies; generalized regenerative model; highly reliable systems; importance sampling; performance measure estimation; refined importance sampling techniques; regenerative simulation; reliability parameter estimation; Failure analysis; Modeling; Monte Carlo methods; Parameter estimation; Random variables; Redundancy; Reliability engineering; Solids; State-space methods; Systems engineering and theory;

fLanguage

English

Publisher

ieee

Conference_Titel

Simulation Conference Proceedings, 1998. Winter

Conference_Location

Washington, DC

Print_ISBN

0-7803-5133-9

Type

conf

DOI

10.1109/WSC.1998.746018

Filename

746018