An Approach for Analyzing Fuzzy System Reliability Using Particle Swarm Optimization and Intuitionistic Fuzzy Set Theory
The main objective of the paper is to present a hybridized technique named as particle swarm optimization based vague cut set (PSOBVCS) for determining the membership and non-membership function of fuzzy system reliability. In the literature so far on the vague set, system reliability is evaluated using a fuzzy arithmetic operation on the collected imprecise, vague or uncertain data. This may contain the wide spread of the reliability and hence cannot give a right decision to decision makers. So in order to remove the uncertainty up to the desired degree, an attempt has been made in this paper in which an expression of system reliability is evaluated using ordinary arithmetic operations instead of fuzzy arithmetic operation and particle swarm optimization has been used to construct their membership functions. The effectiveness of the proposed approach is illustrated with analyze of the fuzzy reliability of series, parallel and series-parallel systems using different types of intuitionistic fuzzy failure rates. The computed results from the analysis have a less range of uncertainty as the comparability of existing results.
Keywords: Vague sets, particle swarm optimization, uncertainty, intuitionistic fuzzy numbers, nonlinear optimization, fuzzy reliability