Enhanced PSO Based on Multi-Agent System

被引：0

作者：

Fang, Luping ^{[1
]}

Ge, Yiming ^{[1
]}

机构：

[1] Zhejiang Univ Technol, Software Coll, Hangzhou 310014, Zhejiang, Peoples R China

来源：

PROCEEDINGS OF THE 2008 INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DESIGN, VOL 1 | 2008年

关键词：

D O I：

10.1109/ISCID.2008.108

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Traditional particle swarm optimization (PSO) algorithm is combined with multi-agent system (MAS), so the particles are upgraded to intelligent agents, which are more autonomous and smart. Secondly, Evolutionary Programming (EP) is integrated into agents to improve the search capability of standard PSO particles by altering their intrinsic tendency of moving to global best position. Thirdly, an adaptive mechanism is proposed to lessen Vmax's impact over algorithm performance, so that the algorithm becomes more feasible. Finally, the enhanced algorithm is applied in the optimization problem of complex functions of high dimension and satisfied results are achieved.

引用

页码：290 / 293

页数：4

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