Abstract: Genetic algorithm and tabu search algorithm are powerful tools to solve the complicated large-scale optimization problems. Through comprehensive contrast and comparison between the above two algorithms, a hybrid optimization algorithm was proposed to improve the local search ability of genetic algorithm. In this algorithm, in order to speed up convergence speed and get satisfied results, tabu search algorithm was applied for local search, and genetic algorithm was used for global search. Meanwhile a strategy was proposed to control prematurity and to avoid converging to local optimum. The test results show that both calculating speed and output are improved