中文摘要：

针对差分进化算法易陷入局部最优及收敛速度慢的缺点,提出基于种群分类的差分进化算法.该算法首先在种群中随机选取3个个体,与目标个体的适应度值进行比较,从而将种群分为优势、一般和劣势子种群;其次对每类子种群采用不同的变异算子进行变异操作,并设置合理的参数取值.所提算法不仅保证了算法的鲁棒性,而且充分利用了每个个体的特征信息,有效地平衡了全局搜索能力和局部开发能力.数值实验说明了本文算法的有效性.

英文摘要：

To prevent differential evolution algorithm from falling into local optimum and reducing the convergence rate,a differential evolution algorithm based on population classification is proposed.The proposed algorithm firstly divides the whole population into three sub-populations（superior,general and inferior sub-populations）by means of chosing three individuals randomly from the population and comparing with target individuals according to their fitness values.Then,three mutation operators with different characteristics are assigned for each subpopulation above according to their special individual information,and control parameters among each mutation operator are suitably adjusted.The proposed algorithm could not only enhance the robustness,but also balance effectively the exploration and exploitation abilities by making full use of the information of individuals.Lastly,the effectiveness of this algorithm is shown by numerical experiments.