Chaotic particle swarm optimization method exploiting sinusoidal perturbations

The particle swarm optimization (PSO) method is a population-based optimization technique which searches for solutions by updating simultaneously a number of candidate solutions called particles. Since, in the PSO, the exploration ability is important to find a desirable solution, various kinds of methods have been investigated to improve it. In this paper, we propose a new chaotic dynamical system for PSO having sinusoidal perturbations, in which chaotic particles can be expected to search for solutions around the two tentative solutions by using chaotic sequences. Through computational experiments, by applying them to some global optimization problems, we compare the proposed chaotic PSO with the standard one.