• DocumentCode
    498783
  • Title

    The impact of population size on the performance of GA

  • Author

    Zhang, Gu-li ; Liu, Xiao-xia ; Zhang, Tong

  • Author_Institution
    Dept. of Math. & Phys., North China Electr. Power Univ., Baoding, China
  • Volume
    4
  • fYear
    2009
  • fDate
    12-15 July 2009
  • Firstpage
    1866
  • Lastpage
    1870
  • Abstract
    The population size is fixed in the traditional genetic algorithm, and nobody knows how much the population size should be taken. In addition, the research on population size is a few. This paper studies mainly population size how to impact on convergence rate, convergence time and global search capability of the genetic algorithm for the typical benchmark functions, and furthermore propose a criterion to evaluate the performance of genetic algorithm. Finally gives some useful conclusions.
  • Keywords
    convergence; genetic algorithms; search problems; genetic algorithm; population size; search capability; typical benchmark function; Algorithm design and analysis; Convergence; Cybernetics; Genetic algorithms; Genetic mutations; Iterative algorithms; Machine learning; Mathematics; Performance analysis; Physics; Convergence rate; Convergence time; Genetic algorithm; Global search capability; Population size;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2009 International Conference on
  • Conference_Location
    Baoding
  • Print_ISBN
    978-1-4244-3702-3
  • Electronic_ISBN
    978-1-4244-3703-0
  • Type

    conf

  • DOI
    10.1109/ICMLC.2009.5212113
  • Filename
    5212113