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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?和交叉率CR,提出?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.
An adaptive distributed differential evolution algorithm is proposed, which divides the initial population into multiple subpopulations and designs the migration mechanism between subpopulations. When the migration conditions are satisfied, according to the von Neumann topological structure, the excellent individuals in the subpopulation Instead of the poor individual in its neighborhood, makes the whole population share information.At the same time, according to the change of individual fitness, each individual is assigned a different scaling factor, and the crossover rate, CR, to propose the adaptive strategy of CR and CR. The results show that the proposed algorithm is beneficial to explore the solution space extensively and avoid the algorithm getting into premature convergence and searching for a better performance solution.