关键词: 粒子群优化, 惯性权重, 位置更新, 多峰函数, 柯西分布

Abstract:

This article uses the Cauchy distribution function and density function respectively to improve the inertia weight and location update formula in view of the local optimal characteristics and slow convergence of traditional particle swarm optimization algorithms.Compared with the standard PSO algorithm and the Cauchy distribution improved inertia weight,the improved algorithm can converge to the global optimal solution quickly.Simulation of four classic test functions shows that the improved algorithm has high precision and good stability of the solution,especially in solving multimodal functions.

Key words: particle swarm optimization;inertia weight;location update;multi peak function;Cauchy distribution