RELIABILITY OPTIMIZATION USING HYBRID GENETIC AND PARTICLE SWARM OPTIMIZATION ALGORITHM

Abstract

Redundancy-allocation problem i.e. RAP is among the reliability optimization problems which make use of non-linear programming method to improve the reliability of complex system. The objective of this research paper is reliability optimization through the application of Genetic Algorithm i.e. GA and Hybrid Genetic & Particle Swarm Optimization (H-GAPSO) on a RAP. Certain shortcomings have been seen when results are obtained by application of single algorithms. In order to get rid of these shortcomings, HGA-PSO is introduced where attractive properties of GA and PSO are combined. This hybrid method makes use of iterative process of GA after obtaining initial best population from PSO. Comparative Analysis of results of GA and H-GAPSO is done with respect to reliability and computation (CPU) time and it is observed that HGAPSO improved system reliability up to maximum by 63.10%. MATLAB programming has been used for computation of results from GA and HGA-PSO algorithms.