New hybrid genetical - Swarm algorithm for electromagnetic optimization

被引：0

作者：

Grimaldi, EA ^{[1
]}

Grimaccia, F ^{[1
]}

Mussetta, M ^{[1
]}

Pirinoli, P ^{[1
]}

Zich, RE ^{[1
]}

机构：

[1] Politecn Milan, Dipartimento Elettrotecn, I-20133 Milan, Italy

来源：

2004 3RD INTERNATIONAL CONFERENCE ON COMPUTATIONAL ELECTROMAGNETICS AND ITS APPLICATIONS, PROCEEDINGS | 2004年

关键词：

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

A new hybrid evolutionary algorithm called GSO (Genetical Swarm Optimization) is here presented. GSO combines the well known Particle Swarm Optimization and Genetic Algorithms. GSO algorithm is essentially a population-based heuristic search technique which can be used to solve combinatorial optimization problems, modeled on the concept of natural selection but also based on cultural and social evolution. A detailed description of the algorithm and numerical comparison of the different techniques are presented for typical electromagnetic optimization problem.

引用

页码：157 / 160

页数：4

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