Abstract: The particle swarm optimization algorithm is a new branch in evolution computing field.This algorithm is simple and effective，and is easy in premature convergence.According to the idea of divide and conquer and the enlightenment of co-evolution，two sub-swarms co-evolution particle swarm optimization algorithm is presented.When it is odd number，the algorithm searches and finds optimization in all particles，else particles are divided into two sub-swarms；they implement their own tasks without almost any connection with others.By doing experiments on four benchmark functions，the results show that the algorithm avoids trapping into local optimum in a certain extent and improves the precision of convergence.

摘要： 针对微粒群优化算法易发生过早收敛问题，受自然界分而治之的思想和共生现象的启发，提出了一种二分微粒群协同进化优化算法，算法的主要思想是在奇数次对种群进行寻优，在偶数次将微粒群分为两个子种群，子种群独立完成寻优任务，与其他群体几乎不发生联系。最后，通过对5个标准函数的测试结果表明，提出的算法在一定程度上避免了陷入局部极值点，并且提高了收敛精度。