Hybrid particle swarm optimization with simulated annealing

Particle swarm optimization is a recently invented intelligent optimizer with several highly desirable attributes. A hybrid particle swarm optimization is proposed. This method integrates the particle swarm optimization with simulated annealing. The method is applied to six test functions´ optimization and the simulation shows that the performance of this algorithm is better than that of the adaptive particle swarm optimization and the genetic chaos optimization.