Abstract: This paper proposed a novel Particle Swarm Optimization (PSO) hybrid algorithm to improve the optimum speed and performance of the PSO algorithm. This new algorithm introduced a dynamic proportion operator into differential evolution algorithm and also introduced mutation, crossover operator from DE algorithm into PSO algorithm. Then the position updating formula of PSO was reconstructed. At last, this paper chose four reference functions to have a test and compared the results with other PSO hybrid algorithms. The simulation results verify the effectiveness of this approach.

Key words: PSO algorithm, differential evolution algorithm, mutation, crossover

摘要： 为了提高粒子群算法的寻优速度和寻优精度,提出一种改进的PSO混合算法。在差分进化(DE)算法中引入了动态比例因子,在PSO算法中引入DE算法的变异、交叉操作,重新构造PSO算法的粒子位置更新公式。选取了4个基准函数进行测试,并与其他PSO混合算法作了比较。仿真结果表明该方法是有效的。

关键词: 粒子群算法, 差分进化算法, 变异, 交叉