Dynamic particle swarm optimization using a wavelet mutation strategy for composite function optimization

In this paper, a novel dynamic particle swarm optimization is considered for composite function optimization. Because the complex computation problem exists commonly in practice, solving this problem is significant. The dynamic neighborhood topology and wavelet mutation could assist the PSO algorithm cooperate with neighbor particles and overcome the premature problem. The results offer insight into how the proposed algorithm has the better effectiveness in solving composite functions.