Abstract: A new algorithm based on continuous mutation was proposed. The mixed selection was used for choosing individuals. Through the combination of the phased crossover and the cosine adaptive crossover, the double adaptive crossover got the crossover probability. The continuous mutation strategy used continuous process from crude search to precise search. Numerical experiments show that the new algorithm is more effective in realizing the high convergence speed, convergence precision, reducing the convergence algebra and good at keeping the stability of the adaptive genetic algorithm.

Key words: mutation, adaptive genetic algorithm, adaptive crossover, selection, Gray code

摘要： 提出了一种新的基于连续变异的自适应遗传算法。利用混合选择策略对个体进行选择,双重自适应交叉将分阶段交叉与正弦自适应交叉方法相结合得到交叉概率，提出的连续变异策略采用连续的粗搜到细搜的过程。数值实验表明：新算法在提高收敛速度和收敛精度、减少收敛代数方面效果显著，稳定性也有所提高。

关键词: 变异, 自适应遗传算法, 自适应交叉, 选择, 格雷码