New chaos-particle swarm optimization algorithm - Xiao-bo XU; Kang-feng ZHENG; Dan LI; Bin WU; Yi-xian YANG (Tongxin xuebao)
The original particle swarm optimization (PSO)algorithm has the advantages of fast convergence,but with the shortcoming of premature and local convergence.To overcome this problem,a new chaos-particle swarm optimization algorithm was presented,which was different from the conventional method of replacing pre-particle.Instead,the algorithm in this paper made the motion of particles with characteristics of chaos，so as to make particles move between the state of chaos and stable,and gradually close to the optimal value.The nonlinear dynamics of the proposed Mathematical model are analyzed,and the results of the experiment show that the proposed algorithm can result in encouraging results.