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The particle swarm optimization (PSO) is one of the best efficient algorithms. It has obtained more and more attention and has been applied in many fields, such as machine design and circuit design. But it also has some disadvantages, such as prematurely and difficultly to convergence. To improvement the performance of PSO, particle reliving strategy is proposed. With this strategy, a criterion is used to judge whether the particle relives. If so, the particle will relive just like that when the algorithm initials. Some benchmark functions are used to illuminate that the successful probability of PSO is improved with particle reliving.