EconPapers    
Economics at your fingertips  
 

Reliability Approximation for Markov Chain Imbeddable Systems

Michael V. Boutsikas () and Markos V. Koutras ()
Additional contact information
Michael V. Boutsikas: University of Piraeus
Markos V. Koutras: University of Piraeus

Methodology and Computing in Applied Probability, 2000, vol. 2, issue 4, 393-411

Abstract: Abstract In the present article, a simple method is developed for approximating the reliability of Markov chain imbeddable systems. The approximating formula reduces the problem to the reliability assessment of smaller systems with structure similar to the original systems. Two specific reliability structures which have attracted considerable research interest recently (r-within-consecutive-k-out-of-n system and two dimensional r-within-k 1 × k 2-out-of-n 1 × n 2 system) are studied by the new approach and numerical calculations are carried out, which reveal the high quality of our approximations. Several possible extensions and generalizations are also presented in brief.

Keywords: reliability approximation; Markov chain imbeddable systems; r-within-consecutive-k-out-of-n system; two dimensional r-within-k 1 × k 2-out-of-n 1 × n 2 system; waiting time distributions (search for similar items in EconPapers)
Date: 2000
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3) Track citations by RSS feed

Downloads: (external link)
http://link.springer.com/10.1023/A:1010062218369 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:metcap:v:2:y:2000:i:4:d:10.1023_a:1010062218369

Ordering information: This journal article can be ordered from
https://www.springer.com/journal/11009

DOI: 10.1023/A:1010062218369

Access Statistics for this article

Methodology and Computing in Applied Probability is currently edited by Joseph Glaz

More articles in Methodology and Computing in Applied Probability from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2022-05-12
Handle: RePEc:spr:metcap:v:2:y:2000:i:4:d:10.1023_a:1010062218369