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
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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.
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页码：157 / 160
页数：4
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