Abstract: The novel Chaos-Genetic Algorithm（CGA） based on the cat map is proposed which combines Genetic Algorithm（GA） and Chaos Algorithm（CA）.This paper explains the ergodicity of the cat map，analyzes the chaotic distributed superiority of the cat map.The algorithm uses the initial sensitivity of the cat map to expand the scope of the search，and uses the ergodicity of the cat map to search the chaotic variables.Thus，the data redundancy is reduced，the diversity of population is maintained，and the problem of local optimum is effectively solved.Theoretical analysis and numerical simulation demonstrate that CGA has better convergence performance.

Key words: Chaos-Genetic Algorithm（CGA）, cat map, ergodicity, adaptive crossover, chaotic mutation

摘要： 将遗传算法与混沌算法相结合，提出了一种新颖的基于猫映射的混沌遗传算法（CGA），解释了猫映射的遍历性，分析了猫映射的混沌分布优越性。该算法利用猫映射的初值敏感性扩大搜索范围，利用猫映射的遍历性进行混沌变量的优化搜索，从而减少了数据冗余，保持了种群多样性，有效地解决了局部收敛问题。理论分析和数值仿真表明，该算法具有更好的收敛性能。

关键词: 混沌遗传算法（CGA）, 猫映射, 遍历性, 自适应交叉, 混沌变异