关键词: 模拟退火, 粒子群优化, 混沌运动

Abstract: To resolve the traditional PSO easily trapped into local optimum problem, it applies the features of chaotic motion, ergodicity, randomness and initial value sensitivity into the process of particle swarm optimization, and by the method of simulated annealing partial optimization of parameters, the parameter of particle swarm optimization algorithm changes continuously with optimization algorithm to adapt to changing optimization needs. The simulation experiments of classic function show that the method can improve the convergence, the convergence accuracy is improved, and it overcomes the problem of falling into local minimum region easily.

Key words: simulated annealing, particle swarm optimization, chaotic motion