Computer Engineering and Applications ›› 2013, Vol. 49 ›› Issue (17): 190-194.

### Multi-objective particle swarm optimization algorithm based on crowding-density

YANG Hu1, XU Feng2

1. 1.School of Computer Science and Engineering, Anhui University of Science and Technology, Huainan, Anhui 232001, China
2.School of Science, Anhui University of Science and Technology, Huainan, Anhui 232001, China
• Online:2013-09-01 Published:2013-09-13

### 基于聚集密度的粒子群多目标优化算法

1. 1.安徽理工大学 计算机科学与工程学院，安徽 淮南 232001
2.安徽理工大学 理学院，安徽 淮南 232001

Abstract: In order to improve the distribution of multi-objective PSO algorithm, crowding-density is introduced for the update of elite set. The basic idea is: the crowding-density of each individual in the group is calculated, and then a partial order set is set up according to the objective function value and crowding-density. Individuals are selected from the partial order set according to the principle of proportional selection, and the elite set is updated. The convergence and distribution of improved algorithm are studied by means of numerical experiments, and results show that the convergence of improved algorithm is roughly equal with the conventional multi-objective particle swarm optimization algorithm, but the distribution of improved algorithm has been significantly improved.