Improvement of particle swarm optimization for high-dimensional space

被引：0
|
作者：
Korenaga, Takeshi [1 ]
Hatanaka, Toshiharu [1 ]
Uosaki, Katsuji [2 ]
机构：
[1] Osaka Univ, Dept Informat & Phys Sci, Osaka, Japan
[2] Fukui Univ Technol, Dept Management & Informat Sci, Fukui, Japan
来源：
2006 SICE-ICASE INTERNATIONAL JOINT CONFERENCE, VOLS 1-13 | 2006年
关键词：
particle swarm optimization; swarm intelligence; diversity; high-dimensional function optimization;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Particle Swarm Optimization (PSO) is a population-based search methodology inspired by social behavior observed in nature, such as flocks of birds and schools of fish. In many studies, PSO has been successful in a variety of optimization problems. The purpose of this paper is to improve performance of the PSO algorithm in case of high-dimensional problems. We propose a novel PSO model, the Rotated Particle Swarm (RPS), which is introduced the coordinate conversion. The numerical simulation results show the RPS is effective in optimizing high-dimensional functions.
引用
收藏
页码：5086 / +
页数：2
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