• DocumentCode
    2244897
  • Title

    An improved genetic algorithm and its performance analysis

  • Author

    Pi, Luo ; Jianfu, Teng ; Jichang, Guo ; Qiang, LI

  • Author_Institution
    Sch. of Electron. & Inf. Eng., Tianjin Univ., China
  • Volume
    4
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    329
  • Abstract
    In the paper, some general theorems-minimal resolution, weight value, and searching step of crossover and mutation of the chromosome searching step in a genetic algorithm based on binary coding, one-point, crossover, and bit mutation are proposed and proved. Based on these theorems, an improved genetic algorithm using variant chromosome length and probability of crossover and mutation is presented. Finally, testing with some critical functions shows that it can improve the convergence speed of the genetic algorithm significantly and it accords with theoretic deduction, and its comprehensive performance is better than that of the genetic algorithm which only reserves the best individual
  • Keywords
    convergence; genetic algorithms; probability; binary coding; bit mutation; convergence speed; improved genetic algorithm; minimal resolution; mutation; one-point crossover; performance analysis; searching; variant chromosome length; weight value; Biological cells; Computational modeling; Convergence; Genetic algorithms; Genetic engineering; Genetic mutations; Parallel processing; Performance analysis; Robustness; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Info-tech and Info-net, 2001. Proceedings. ICII 2001 - Beijing. 2001 International Conferences on
  • Conference_Location
    Beijing
  • Print_ISBN
    0-7803-7010-4
  • Type

    conf

  • DOI
    10.1109/ICII.2001.983840
  • Filename
    983840