DocumentCode :
175802
Title :
Genetic-Ant Colony Optimization algorithm and its application to design of antenna
Author :
Yan Yang ; Shijun Yan ; Jianxia Liu ; Jun Liang
Author_Institution :
Coll. of Inf. Eng., Taiyuan Univ. of Technol., Taiyuan, China
fYear :
2014
fDate :
19-21 Aug. 2014
Firstpage :
611
Lastpage :
616
Abstract :
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.
Keywords :
ant colony optimisation; broadband antennas; genetic algorithms; microstrip antennas; multifrequency antennas; ACO algorithm; GA; HFSS; U-slot; broadband antenna; dual-band antenna; electromagnetic simulation software; global continuous optimization problem; hybrid GACO algorithm; hybrid genetic-ant colony optimization algorithm; rectangular microstrip patch antenna design; Algorithm design and analysis; Genetic algorithms; Genetics; Microstrip; Microstrip antennas; Optimization; Genetic-Ant Colony optimization algorithm; HFSS; VBScript; antenna design;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation (ICNC), 2014 10th International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4799-5150-5
Type :
conf
DOI :
10.1109/ICNC.2014.6975905
Filename :
6975905
Link To Document :
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