遗传算法是一种全局优化算法,能以较大概率搜索到全局最优解。本文将Alopex算子嵌入到保留最优个体遗传算法(EGA)中,对非可微或求导困难函数从而得到既能以较大概率搜索全局极值,又能进行局部细致搜索的混合全局优化算法;并对其全局收敛性和计算效率作了证明与分析。数值计算结果表明该算法优于求解函数优化的EGA和Alopex算法。 Genetic algorithm is a kind of global optimization algorithm, which can search the global optimal solution with a high probability. In this paper, we embed Alopex operator into the reserved optimal individual genetic algorithm (EGA), and obtain the non-differentiable or derivative-hard functions so as to obtain the global optimization with both high probability of searching global extremum and local detailed search Algorithm; and proved its global convergence and computational efficiency. The numerical results show that the proposed algorithm is better than the EGA and Alopex algorithm for solving function optimization.