Statistic Analysis on Parameter Efficiency of Particle Swarm Optimization

Satisfactory results have been acquired in functional and combinational optimization by adopting particle swarm optimization.Its significant feature is simpler expression,less parameters and easier operation.However,selection of key parameters has great influence on algorithm effects.So the variance analysis of statistic theory is applied to analyze the effect of inertia weight and accelerating constants.It was proved that robust and effective optimization can be achieved by setting parameters according to the variance analysis results discussed.