Title :
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
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;
Conference_Titel :
Simulation Conference Proceedings, 1998. Winter
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-5133-9
DOI :
10.1109/WSC.1998.746018
