A novel chaotic PSO algorithm based on tent map and its application to mechanical design

To prevent the Particle Swarm Optimization algorithm (PSO) plunging into the local minima with low convergence speed in the later stage of iteration, especially for multimodal functions with lots of local minima, a novel hybrid algorithm combining PSO with the chaotic optimization algorithm based on Tent map is proposed in this paper. In view of the advantages of Tent map, the chaotic sequences generated by it are used to implement chaotic searching at zones nearby individual and global optimum points for particles escaping from the local minima. Optimization results of typical test functions and practical application in mechanical design show that the new algorithm has higher global search capability, convergence precision and faster speed for multimodal functions. Copyright © 2013 Binary Information Press.