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中文摘要：
提出一种适应性分布式差分进化算法．将初始种群分为多个子种群，并设计子种群间的迁移机制，当满足迁移条件时，根据冯·诺依曼拓扑结构，子种群内的优秀个体代替其邻域的较差个体，使得整个种群实现信息共享．同时，根据个体适应值变化情况，对每一个体分配不同的缩放因子F和交叉率CR，提出F和CR的适应性策略．实验结果表明，所提出算法有利于对解空间进行广泛探索，避免算法陷入早熟收敛，能够搜索到性能较好的解．
英文摘要：
An adaptive distributed differential evolution algorithm is proposed based on the change of the individual＇s fitness value. Firstly, the initial population is divided into several subpopulations. When the migration condition is satisfied, the best individual in each subpopulation will replace the worst individual of its neighbor subpopulations according to the Von Neumann topology. The migration mechanism among subpopulations enables the information to be communicated in the whole population. Meanwhile, the adaptive mechanism of F and CR is presented for assigning different F and CR to each individual according to the individual＇s fitness. Numerical results show that, the proposed algorithm is beneficial to explore the solution space, which can avoid the premature convergence and search the excellent solutions.
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