摘要： 结合粒子群优化(PSO)算法和人工鱼群算法(AFSA)的优势，提出一种PSO-AFSA混合算法。将种群分为2个子群体，在每次迭代中，一个子群体利用PSO算法进化，另一个子群体利用AFSA进化，2个算法共享整个种群极值信息。通过混合算法对5个标准函数进行实验，并与标准PSO算法进行比较，结果表明混合算法具有更好的优化性能。

关键词: 粒子群优化算法, 人工鱼群算法, PSO-AFSA混合算法, 群体智能

Abstract: This paper proposes a hybrid algorithm of Particle Swarm Optimization(PSO) and Artificial Fish Swarm Algorithm(AFSA) by combining the advantages of PSO algorithm and AFSA. Hybrid algorithm divides the swarm into two sub-groups. In each iteration, one sub-group evolves using PSO algorithm, the other sub-group evolves using AFSA, and two algorithms share the information of groups extremum. Through comparing PSO-AFSA hybrid algorithm with standard PSO algorithm in evolving solution to five standard functions, results show that PSO-AFSA hybrid algorithm outperforms PSO algorithm.

Key words: Particle Swarm Optimization(PSO) algorithm, Artificial Fish Swarm Algorithm(AFSA), PSO-AFSA hybrid algorithm, swarm intelligence

中图分类号: 

• TP18