• 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