Cooperative Fuzzy Particle Swarm Optimization

Particle swarm optimization is a population based optimization technique that is based on probability rules. In this technique each particle moves toward their best individual and group experience had occurred. Fundamental problems of standard PSO algorithm are the falling into the trap of local optimum and its low speed of convergence. One approach for solving the above problems is to combine fuzzy logics with PSO. In this paper we first use fuzzy logic to improve standard PSO and then use it in cooperative particle swarm optimization. For evaluation purpose, the proposed algorithms are tested on number of standard optimization functions and the results obtained are compared with the results for the existing algorithms. The results of comparisons have shown the superiority of the proposed algorithm over existing algorithms.