中文摘要：

针对传统进化算法的早熟和收敛速度慢等瓶颈问题，提出了自适应混沌量子克隆算法．算法中采用量子编码来表示个体，利用个体质量、进化代数和个体的分布情况构造变异算子，针对克隆算子局部寻优能力强的特点，通过logistic混沌序列自适应地调节变异尺度，提高种群多样性，避免盲目搜索．对函数优化问题的仿真实验表明：本算法求解精度高，均方差小于10；运算次数小，平均运算代数在10代以内就能获得高质量的解．

英文摘要：

A novel algorithm, called the self-adaptive chaos quantum clonal algorithms-SCQA, is proposed to avoid premature convergence. By adopting the quantum bit as a representation, SCQA uses the Logistic Sequence to control the mutation size and Chaos Mutation Operator to control the clonal selection. Simulations with function optimization problems show that SCQA performs well in terms of the quality of solution and computational cost,where the standard deviation is up to 10^-7 and the number of the mean generations is less than 10.