Title :
An O(n·(log2(n))2) algorithm for computing the reliability of k-out-of-n:G and k-to-l-out-of-n:G systems
Author :
Belfore, Lee A., II
Author_Institution :
Dept. of Electr. & Comput. Eng., Marquette Univ., Milwaukee, WI, USA
fDate :
3/1/1995 12:00:00 AM
Abstract :
This paper presents the RAFFT-GFP (Recursively Applied Fast Fourier Transform for Generator Function Products) algorithm as a computationally superior algorithm for expressing and computing the reliability of k-out-of-n:G and k-to-l-out-of-n:G systems using the fast Fourier transform. Originally suggested by Barlow and Heidtmann (1984), generating functions provide a clear, concise method for computing the reliabilities of such systems. By recursively applying the FFT to computing generator function products, the RAFFT-GFP achieves an overall asymptotic computational complexity of O(n·(log2(n)) 2) for computing system reliability. Algebraic manipulations suggested by Upadhyaya and Pham (1993) are reformulated in the context of generator functions to reduce the number of computations. The number of computations and the CPU time are used to compare the performance of the RAFFT-GFP algorithm to the best found in the literature. Due to larger overheads required, the RAFFT-GFP algorithm is superior for problem sizes larger than about 4000 components, in terms of both computation and CPU time for the examples studied in this paper. Lastly, studies of very large systems with unequal reliabilities indicate that the binomial distribution gives a good approximation for generating function coefficients, allowing algebraic solutions for system reliability
Keywords :
binomial distribution; computational complexity; consecutive system reliability; fast Fourier transforms; reliability theory; CPU time; Generator Function Products; O(n·(log2(n))2) algorithm; Recursively Applied Fast Fourier Transform; algebraic manipulations; asymptotic computational complexity; binomial distribution; k-out-of-n:G system; k-to-l-out-of-n:G system; performance comparison; reliability computation; unequal reliabilities; Algorithm design and analysis; Central Processing Unit; Computational complexity; Computational efficiency; Convolution; Fast Fourier transforms; Mathematics; Polynomials; Reliability theory;
Journal_Title :
Reliability, IEEE Transactions on