Evaluation of a competitive particle swarm optimizer in multimodal functions with complexity

被引：0

作者：

Taguchi, Yu ^{[1
]}

Nakano, Hidehiro ^{[1
]}

Utani, Akihide ^{[1
]}

Miyauchi, Arata ^{[1
]}

Yamamoto, Hisao ^{[1
]}

机构：

[1] Tokyo City Univ, Setagaya Ku, 1-28-1 Tamazutsumi, Tokyo 1588557, Japan

来源：

PROCEEDINGS OF THE SIXTEENTH INTERNATIONAL SYMPOSIUM ON ARTIFICIAL LIFE AND ROBOTICS (AROB 16TH '11) | 2011年

关键词：

Particle Swarm Optimization; Optimization Problems; Plural Solutions;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we present a simple competitive particle swarm optimizer (CPSO) for finding plural solutions. In the CPSO, particles are divided into groups corresponding to the required number of solutions. Each group simultaneously searches solutions having a priority search region. This region affects to prohibit that different groups search the same solutions. The CPSO can effectively find desired plural acceptable solutions with a high accuracy and with a low computation cost, and can easily control combinations of these solutions by adjusting a parameter. This paper evaluates the CPSO in complex global optimization benchmarks. Through the numerical experiments, searching performances of the CPSO are clarified.

引用

页码：707 / 710

页数：4

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