摘要： 单一结构和机制的算法一般难以得到满意的解。为此，提出一种新型的启发式人工鱼群算法。将进化策略、粒子群算法中的信息策略加入到人工鱼群算法中，并在理论上证明该算法的收敛性。函数仿真实验表明，该算法可以避免基本人工鱼群算法陷入局部极值，且具有收敛速度快、计算精度高等特点。

关键词: 启发式信息, 工鱼群算法, 子群优化, 化策略, 数估计

Abstract: It is a difficulty to obtain satisfactory solution based on a single structure and mechanism generally. Adding heuristic information of Evolutionary Strategy(ES) and Particle Swarm Optimization(PSO) to artificial fish swarm algorithm, a novel Artificial Fish Swarm Algorithm(AFSA) is proposed. Its convergence is proved. Experimental results show that the algorithm can effectively avoid the basic AFSA into local extremum. It can converge quickly with high adjustment and the effectiveness is also demonstrated by parameter estimation.

Key words: heuristic information, Artificial Fish Swarm Algorithm(AFSA), Particle Swarm Optimization(PSO), Evolutionary Strategy(ES), parameter estimation

中图分类号: 

• TP18