计算机工程与应用2019，Vol.55Issue(5)：166-174,9.DOI:10.3778/j.issn.1002-8331.1711-0358
基于个体邻域的改进NSGA-II算法
Improved NSGA-II Algorithm Based on Individual Neighborhood
摘要
Abstract
The Non-dominated Sorting Genetic Algorithm with elite strategy(NSGA-II)based on NSGA is one of the classical algorithms to solve multi-objective optimization problems. Congestion and congestion comparison operator are proposed by NSGA-II, which replace the fitness sharing strategy which needs to specify the shared radius. However, the exclusion mechanism based on crowding distance in NSGA-II to maintain population diversity has a defect in the front of the pareto frontier. Therefore, an improved algorithm named SN-NSGA2 which considers individual neighborhood is proposed. The idea of neighborhood in the density clustering algorithm DBSCAN is applied to new exclusion mechanism, and simultaneously a method of constructing individual neighborhood with corresponding elimination strategy is put forward. Experimental results show that the new algorithm has better distribution and good convergence.关键词
带有精英策略的非支配排序遗传算法(NSGA2)/多目标优化/邻域/分布性/拥挤距离Key words
Non-dominated Sorting Genetic Algorithm with elite strategy(NSGA2)/ multiobjective optimization/ neigh-borhood/ diversity/ crowding distance分类
信息技术与安全科学引用本文复制引用
董骏峰,王祥,梁昌勇..基于个体邻域的改进NSGA-II算法[J].计算机工程与应用,2019,55(5):166-174,9.基金项目
山东省科技发展计划项目(No.2014GGX101011) （No.2014GGX101011）
山东建筑大学博士基金(No.XNBS1523) （No.XNBS1523）
济南市软科学计划项目(No.201704065). （No.201704065）
