Abstract: The artificial fish school algorithm is a swarm intelligence stochastic global optimization algorithm.However it falls into the local optimum solution and the efficiency low frequently.Using chaos search characteristic，a novel artificial fish school algorithm based on chaos search is proposed in this paper.Initialize population of fish with the chaos，after swarm behavior and follow behavior，they carry on the chaos search to enable artificial fish to get rid of local minima and improve efficiency.Several computer simulation results show that the proposed algorithm is stronger than the basic artificial fish school algorithm in global optimization ability，and the search efficiency is higher.

摘要： 人工鱼群算法是一种群智能全局随机优化算法，存在陷入局部极值和效率低的不足，结合混沌搜索的特点，提出一种混沌人工鱼群优化算法，该算法是用混沌初始化来初始化鱼群，在聚群和追尾行为后进行混沌的遍历性和随机性扰动来使鱼群局部搜索同时摆脱局部极值点。仿真实验结果表明，该算法比基本人工鱼群算法全局能力更强，搜索效率更高。