基于混沌映射的元胞遗传算法  

Cellular Genetic Algorithm Based on Chaotic Map

作　　者：李雪岩[1] 李雪梅[1] 李学伟[1] 吴今培[2] 

机构地区：[1]北京交通大学经济管理学院,北京100044 [2]五邑大学智能技术与系统研究所,江门529020

出　　处：《模式识别与人工智能》2015年第1期42-49,共8页Pattern Recognition and Artificial Intelligence

基　　金：国家自然科学基金项目(No.71273023);高等学校博士学科点专项科研基金项目(No.20130009110020)资助

摘　　要：针对元胞遗传算法(CGA)的功能及结构特点,将元胞遗传算法与混沌算法进行有机结合,分别设计基于Cat映射、Logistic映射及Tent映射的混沌映射元胞遗传算法(CCGA),并解释三种映射的遍历性.文中利用混沌映射的遍历特点及初值敏感性优化种群的初始分布,扩大搜索范围,设计遗传算子中的局部混沌交叉操作及混沌变异扰动机制,并比较不同混沌映射算子作用下种群多样性的变化.理论分析及计算机仿真实验表明,引入三种混沌映射的元胞遗传算法在提升寻优精度,提高算法收敛速度,避免局部极值方面均取得良好的效果.According to the function and structure characteristics of cellular genetic algorithm （CGA）, chaos cellular genetic algorithm （CCGA） based on Cat map, Logistic map and Tent map are designed respectively with the organic combination of cellular genetic algorithm and chaos algorithm. Besides, the ergodicity of three chaotic mappings are explained. Taking advantage of chaotic ergodicity and sensitivity to initial condition, the initial distribution of population is optimized, the searching scope of the algorithm is enlarged, the mechanism of local chaotic crossover operator and chaotic mutation disturbance are designed, and the changes of population diversity are compared under different mapping operators Theoretical analysis and simulation results show that the proposed algorithm has obtained good performance in improving optimizing accuracy, accelerating convergence and avoiding the local optimum by introducing three chaotic maps.

关 键 词：元胞遗传算法(CGA) 种群分布 局部混沌交叉 混沌变异 混沌映射 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]