计算机应用与软件Issue(10)：317-321,5.DOI:10.3969/j.issn.1000-386x.2013.10.086
多目标进化算法中基于聚集距离调整的分布性保持方法
CROWDING DISTANCE ADJUSTMENT-BASED DISTRIBUTION PROPERTY MAINTENANCE STRATEGY IN MOEAS
蒲骁旻1
作者信息
- 1. 湖南工业职业技术学院信息工程系 湖南 长沙410208
- 折叠
摘要
Abstract
In classical non-dominated sorting genetic algorithm,population maintenance strategies based on crowding distance can not well maintain the distribution property of its solutions.We propose an improved distribution property maintenance strategy.It is based on crowding distance adjustment and reserves the well-distributed individual solutions according to the size relation of the crowing distance of adjacent indi-viduals.Compared with classical NSGA-Ⅱ,PESA-Ⅱand NICHE,the experimental results demonstrate that the proposed distribution proper-ty maintenance strategy can improve the distribution property to a greater extent and keep better convergence at the same time.关键词
多目标进化算法/聚集距离/分布性维护/Pareto最优解Key words
Multi-objective evolutionary algorithm(MOEA)/Crowding distance/Distribution property maintenance/Pareto optimal solu-tion分类
信息技术与安全科学引用本文复制引用
蒲骁旻..多目标进化算法中基于聚集距离调整的分布性保持方法[J].计算机应用与软件,2013,(10):317-321,5.
