Computer Engineering and Applications ›› 2019, Vol. 55 ›› Issue (5): 166-174.

### Improved NSGA-II Algorithm Based on Individual Neighborhood

DONG Junfeng, WANG Xiang, LIANG Changyong

1. School of Management, Hefei University of Technology, Hefei 230009, China
• Online:2019-03-01 Published:2019-03-06

### 基于个体邻域的改进NSGA-II算法

1. 合肥工业大学 管理学院，合肥 230009

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.