A New Fuzzy Inertia Weight Particle Swarm Optimization

This paper proposes a new fuzzy tuned inertia weight particle swarm optimization (FIPSO) which remarkably outperforms the standard PSO, previous fuzzy as well as adaptive based PSO methods. Two benchmark functions with asymmetric initial range settings are used to validate the proposed algorithm and compare its performance with those of the other tuned parameter PSO algorithms. Numerical results indicate that FIPSO is competitive due to its ability to increase search space diversity as well as finding the functionspsila global optima and a better convergence performance.