Improved particle swarm optimization algorithms for electromagnetic optimization

被引：5

作者：

Mussetta, Marco ^{[1
]}

Selleri, Stefano ^{[2
]}

Pirinoli, Paola ^{[3
]}

Zich, Riccardo E. ^{[1
]}

Matekovits, Ladislau ^{[3
]}

机构：

[1] Politecn Milan, DEE, I-20133 Milan, Italy

[2] Univ Florence, DET, I-50134 Florence, Italy

[3] Politecn Torino, DEE, I-10129 Turin, Italy

来源：

JOURNAL OF INTELLIGENT & FUZZY SYSTEMS | 2008年 / 19卷 / 01期

关键词：

genetic algorithm; particle swarm; optimization;

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：

Particle Swarm is a relatively novel approach for global stochastic optimization. In this paper some variations over the basic algorithm are proposed, with the aim of a more efficient search over the solution space obtained with a negligible overhead in both complexity and speed. The presented algorithms are then applied to a mathematical test function and to a microwave microstrip filter to show their superior capabilities with respect to the conventional version.

引用

页码：75 / 84

页数：10

共 22 条

[1] An Overview of Evolutionary Algorithms for Parameter Optimization [J].