一种简化的人工鱼群算法  

Simplified Artificial Fish Swarm Algorithm

作　　者：王联国[1,2] 洪毅[1] 赵付青[1] 余冬梅[1] 

机构地区：[1]兰州理工大学电气工程与信息工程学院,甘肃兰州730030 [2]甘肃农业大学信息科学技术学院,甘肃兰州730070

出　　处：《小型微型计算机系统》2009年第8期1663-1667,共5页Journal of Chinese Computer Systems

基　　金：甘肃省教育厅科研项目(0602-12)资助

摘　　要：针对人工鱼群算法(AFSA)优化精度低,运行时间长的问题,对其进行了简化,给出人工鱼群算法进化方程,提出一种简化的人工鱼群算法(SAFSA).SAFSA算法在一次迭代进化中同时根据人工鱼觅食结果、种群中心位置和种群最优位置,调整下一步位置,保证算法向全局最优位置移动,同时由于觅食行为中有随机游动现象,使算法具有跳出局部极值的能力,增强了算法的全局搜索能力.仿真结果表明,简化的人工鱼群算法优化效果明显,运行速度快.This paper simplifies AFSA, presents evolution equation of AFSA, and then proposes a simplified artifical fish swarm algorithm （SAFSA）,which is aimed at some defects of AFSA, such as low optimization precision and long running time. According to the preying,the center position and the optimal position of the fish swarm, SAFSA adjusts the next position during the same iterative evolution,so as to ensure that the algorithm will move to the global optimal position, at the same time because AFS swims stochastically just as preying, the algorithm could skip over the local extremum,so as to enhance the global searching ability of it. The simulation results show that optimization effects of the simplified algorithm are obvious and the running speed of that is higher than before.

关 键 词：人工鱼群算法 人工鱼 群体智能 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]