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

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.

Key words: Non-dominated Sorting Genetic Algorithm with elite strategy（NSGA2）, multiobjective optimization, neighborhood, diversity, crowding distance