Abstract: According to the fact that Genetic Algorithm can give generally the better solution in the smaller feasible domain，a hybrid algorithm is presented.The proposed algorithm firstly uses the interval method to obtain all small intervals for the global optimization，then employs the Genetic Algorithm to execute the later process.The hybrid algorithm can reduce efficiently the larger feasible domain，provides the initial population with high fitness，gives all optima of multi-peak optimization，improves the accuracy and avoid falling into local optimum.Finally，numerical experiments show that the algorithm works efficiently.

Key words: Genetic Algorithm, interval method, global optimization

摘要： 根据遗传算法在较小的可行区域内一般有较好的求解结果这一事实，提出了一种混合算法。该算法先利用区间算法求解全局优化问题来得到包含所有最优解的小区间，随后运用遗传算法进行后续过程。算法能够有效缩小一个较大的可行区域空间，提供高适应值的初始种群，求出多峰值问题的全部最优解，提高算法的求解精度同时避免陷入局部最优。最后数值实验说明了算法的有效性。

关键词: 遗传算法, 区间算法, 全局优化