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To improve the performance of Gravitational Search Algorithm (GSA) for box-constrained optimization problems, an improved algorithm based on self-adaptive gravitational search algorithm was proposed. Stagnation coefficient and similarity coefficient are defined. When algorithm has been in stagnation behavior, gravitation parameter is revised adaptively to jump out of stage of stagnation. When swarm fall into local optimal, diversity of swarm will be improved by mutation strategy. The numerical experiment on benchmark functions shows that the improve algorithm efficiently balances the exploit and explorer, especially suitable for solving high dimension and multimodal function optimization problem,