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An evolutionary mechanism of local-competing and global-cooperating is presented for cooperative parallel mechanism based multi-particle-swarm optimizer (CP-MPSO), the competitive relationship between the particles of the traditional serial particle swarm optimizer is analyzed. A weighted-best-information based the PSO with cooperation-characteristic is proposed. Finally, the implementation of CP-MPSO is showed and its time-complexity is analyzed. The experiment results show that the optimizer has obvious advantages, both in the convergence velocity and in the global convergence performance, compared with the standard PSO.