Performance Comparison of Parallel PSO-GA Algorithm with Dynamic Parameter Adjustment Using Type-1 and Interval Type-2 Fuzzy Systems

This paper reveals a comparison between different optimization methods with dynamical adjustment of parameters using Type-1 and interval Type-2 Fuzzy logic systems. In addition, the use of migration blocks in the PSO and Genetic Algorithm (GA) optimization methods is used to help each other to reach the best possible solution, which is also investigated in detail. The hybrid PSO-GA approach offers good simulation results outperforming individually the PSO and GA methods.