Particle Swarm Optimization with Dynamic Neighborhood Topology: Three Neighborhood Strategies and Preliminary Results

被引：0

作者：

Akat, S. Burak ^{[1
]}

Gazi, Veysel ^{[1
]}

机构：

[1] Tobb Univ Econ & Technol, Dept Elect & Elect Engn, TR-06560 Ankara, Turkey

来源：

2008 IEEE SWARM INTELLIGENCE SYMPOSIUM | 2008年

关键词：

Distance Based Neighborhood; Dynamic Neighborhood; Particle Swarm Optimization; Random Neighborhood;

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 article we consider a particle swarm optimization (PSO) algorithm in which the neighbors of the particles or basically the neighborhood topology dynamically changes with time. We consider probabilistic and distance based approaches for determining the neighbors of the particles and represent the dynamic neighborhood topology by a time varying graph. Simulations of several benchmark functions are performed in order to verify the effectiveness of the algorithm.

引用

页码：152 / 159

页数：8

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