標題: | Bootstrapping comparison on availability of parallel systems with non-identical components |
作者: | Ke, Jau-Chuan Chu, Yunn-Kuang Lee, Jia-Huei 工業工程與管理學系 Department of Industrial Engineering and Management |
關鍵字: | Computer bootstrapping;Parallel machines;Simulation |
公開日期: | 2008 |
摘要: | Purpose - In order to develop a feasible and efficient method to acquire the long-run availability of a parallel system with distribution-free up and down times, the purpose of this paper is to perform the simulation comparisons on the interval estimations of system availability using four bootstrapping methods. Desigri/methodology/approach - By using four bootstrap methods; standard bootstrap (SB) confidence interval, percentile bootstrap (PB) confidence interval, bias-corrected percentile bootstrap (BCPB) confidence interval, and bias-corrected and accelerated (BCa) confidence interval. A numerical simulation study is carried out in order to demonstrate performance of these proposed bootstrap confidence intervals. Especially, we investigate the accuracy of the four bootstrap confidence intervals by calculating the coverage percentage, the average length, and the relative coverage of confidence intervals. Findings - Among the four bootstrap confidence intervals, the PB method has the largest relative coverage in most situations. That is, the PB method is the best one made by practitioners who want to obtain an efficient interval estimation of availability. Originality/value - It is the first time that the relative coverage is introduced to evaluate the performance of estimation method, which is more efficient than the existing measures. |
URI: | http://hdl.handle.net/11536/9972 http://dx.doi.org/10.1108/02644400810909625 |
ISSN: | 0264-4401 |
DOI: | 10.1108/02644400810909625 |
期刊: | ENGINEERING COMPUTATIONS |
Volume: | 25 |
Issue: | 7-8 |
起始頁: | 801 |
結束頁: | 816 |
Appears in Collections: | Articles |
Files in This Item:
If it is a zip file, please download the file and unzip it, then open index.html in a browser to view the full text content.