Adaptive particle swarm optimization based on colony fitness variance
Zhao Tian · Computer Engineering and Applications Journal · 2010
Particle Swarm Optimization(PSO) is a novel stochastic global optimization evolutionary algorithm.To overcome the poor stability and local convergence of PSO,an adaptive particle swarm optimization based on colony fitness variance(FV-APSO) is proposed.On the one hand,the uniformly distributed particles are generated in the feasible region by chaos so as to improve the quality of the initial solutions.On the other hand,the adaptive transformation formula of the inertia weight,which is based on fitness variance of swarm is constructed in order to enhance the ability of the PSO to get away from the local optimum.Simulation results show that the FV-APSO is feasible and effective.