Abstract: A hybrid global optimization algorithm is proposed by the Population Migration Algorithm（PMA） and Simplex Algorithm（SA），and it solves the PMA’s problems of premature convergence and slow computation precision.Every point which is produced randomly by PMA is optimized by SA at first.Through a typical test function（Shaffer） to verify the performance of the improved algorithm and 10 types of particle swarm optimization algorithm for comparison，results show that：The algorithm can obtain relatively good solutions，the success rate of convergence is up to 100%.

摘要： 针对基本人口迁移算法具有易早熟和精度不高等缺陷，利用人口迁移算法随机产生的点采用单纯形法进行优化，提出了一种基于单纯形法和人口迁移算法的混合全局优化算法。通过典型的测试函数Shaffer，验证了改进后算法的性能，并与10种类型的粒子群优化算法进行比较，结果表明，该文算法能获得比较好的解，收敛成功率高达100%。