As the gravitational search algorithm plays bad performance in search accuracy of the complex issues,especially the poor search quality of standard Gravitational Search Algorithm (GSA) in the high dimensional function optimization. It is easy to get into premature convergence in the optimization process. Therefore, the idea of the particle swarm optimization algorithm was introduced to gravitational search algorithm, which was used to improve the memory of particles. The particle evolution is not only influenced by other particles in the space, but also by its own memory constraint, which is used to improve the ability of exploitation. The test of the 10 benchmark functions confirms the validity of the method.