• DocumentCode
    775138
  • Title

    An introduction to genetic algorithms for electromagnetics

  • Author

    Haupt, Randy L.

  • Author_Institution
    Dept. of Electr. Eng., US Air Force Acad., Colorado Springs, CO, USA
  • Volume
    37
  • Issue
    2
  • fYear
    1995
  • fDate
    4/1/1995 12:00:00 AM
  • Firstpage
    7
  • Lastpage
    15
  • Abstract
    This article is a tutorial on using genetic algorithms to optimize antenna and scattering patterns. Genetic algorithms are “global” numerical-optimization methods, patterned after the natural processes of genetic recombination and evolution. The algorithms encode each parameter into binary sequences, called a gene, and a set of genes is a chromosome. These chromosomes undergo natural selection, mating, and mutation, to arrive at the final optimal solution. After providing a detailed explanation of how a genetic algorithm works, and a listing of a MATLAB code, the article presents three examples. These examples demonstrate how to optimize antenna patterns and backscattering radar-cross-section patterns. Finally, additional details about algorithm design are given
  • Keywords
    antenna radiation patterns; backscatter; binary sequences; complete computer programs; electrical engineering; electrical engineering computing; electromagnetic wave scattering; genetic algorithms; radar cross-sections; MATLAB code; algorithm design; antenna patterns optimisation; backscattering radar-cross-section patterns; binary sequences; chromosome; electromagnetics; evolution; gene; genetic algorithms; genetic recombination; mating; mutation; natural processes; natural selection; numerical-optimization methods; optimal solution; scattering patterns optimisation; tutorial; Algorithm design and analysis; Animals; Antenna radiation patterns; Biological cells; Electromagnetic forces; Electromagnetic scattering; Genetic algorithms; Radar scattering; Simulated annealing; Solid modeling;
  • fLanguage
    English
  • Journal_Title
    Antennas and Propagation Magazine, IEEE
  • Publisher
    ieee
  • ISSN
    1045-9243
  • Type

    jour

  • DOI
    10.1109/74.382334
  • Filename
    382334