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

页码：5086 / +

页数：2

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