Genetic-Ant Colony Optimization Algorithm and its Application to Design of Antenna

被引：0
|
作者：
Yang, Yan [1 ]
Liu, Jianxia [1 ]
Yan, Shijun [1 ]
Liang, Jun [1 ]
机构：
[1] Taiyuan Univ Technol, Coll Informat Engn, Taiyuan, Peoples R China
来源：
2014 10TH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION (ICNC) | 2014年
关键词：
Genetic-Ant Colony optimization algorithm; antenna design; HFSS; VBScript;
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：
A hybrid Genetic-Ant Colony Optimization (GACO) algorithm is presented and applied in antenna design. The hybrid algorithm is hybridization between Ant Colony Optimization (ACO) algorithm and Genetic algorithm (GA). The algorithm adopts the ability of ACO algorithm to quickly search and the advantage of Genetic Algorithm (GA) to globally search. Therefore it avoids the behavior of ACO to fall into local optimum, and also can be applied to the global continuous optimization problem. In this paper the hybrid algorithm is combined with HFSS (An electromagnetic simulation software) to be applied to design of antenna. The method is illustrated with an example: the design of rectangular microstrip patch antenna with a U-slot for dual band antenna and broad band antenna.
引用
收藏
页码：611 / 616
页数：6
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