基于混沌理论的免疫遗传算法  

Immune genetic algorithm based on chaos theory

作　　者：张楠[1] 李志蜀[2] 张建华[2] 李奇[1] 

机构地区：[1]四川师范大学计算机软件实验室,四川成都610068 [2]四川大学计算机学院,四川成都610065

出　　处：《计算机应用》2006年第5期1111-1112,1115,共3页journal of Computer Applications

摘　　要：为提高免疫遗传算法的运算效率,根据免疫系统本身的混沌特性,提出了一种混沌免疫遗传算法。该算法利用混沌系统的遍历性来减少数据冗余,利用混沌系统的初值敏感性来扩大搜索范围,从而保持了种群的多样性,避免了局部最优。实验表明,该算法比传统的免疫遗传算法具有更高的收敛速度及收敛性能。To increase operating efficiency of immune genetic algorithm, a chaos immune genetic algorithm is presented based on the chaotic character of the immune system. The over-spread character of the chaos sequence was used to overcome redundancies, and the chaos initial value sensitivity was used to enlarge the searching space. Thus, the diversity of population was retained and the local optimization was avoided. The experimental results show that the chaos immune genetic algorithm evidently improves the convergent speed and astringency.

关 键 词：免疫遗传算法 混沌 熵 变异 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]