【摘要】 保持解集的多样性和分布性是多目标进化算法的关键之一。在NSGA-Ⅱ的基础上,提出了一种用混合距离来估计个体的拥挤度,并使用优先队列根据个体的混合距离来逐个删除种群中超出的非劣解以保持解的多样性,实验结果表明,HD-NS-GA-Ⅱ比NSGA-Ⅱ的解分布的更加合理且分布度有很大的提高。更多还原

【Abstract】 Preserving the diversity of solution is a key for multi-objective evolution algorithm.This paper improves of NSGA-II,it suggests a new approach to measure individual crowding distance by hybrid distance and uses priority queue to prune the over-plus of non-dominated solution one by one according hybrid distance for preserving the diversity of solution.Experimental results show that the HD-NSGA-Ⅱ can obtain reasonable distributing solution and diversity of this algorithm are more efficient than NSGA-Ⅱ.更多还原