• DocumentCode
    2567000
  • Title

    A sort-based improved real-code genetic algorithm

  • Author

    Gao Xian-wen ; Zhang Guo-hui

  • Author_Institution
    Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang
  • fYear
    2008
  • fDate
    2-4 July 2008
  • Firstpage
    3877
  • Lastpage
    3881
  • Abstract
    As an adaptive global optimize method by probabilistic search, genetic algorithm had been comprehensively used in many engineering realms. But some disadvantages of this method such as slow convergence speed and local optimization confined further applications. Improved genetic algorithm in speed of convergence and the rate of obtain the optimal solution improved significantly by combine and sort parent-child generations, applying improved proportional selection, anticipative crossover, additive gauss-mutation and so on. Improved genetic algorithm has excellent performance, good universality, suitable for promotion and application.
  • Keywords
    genetic algorithms; adaptive global optimize method; probabilistic search; sort-based improved real-code genetic algorithm; Educational institutions; Electronic mail; Gaussian processes; Genetic algorithms; Genetic engineering; Information science; Optimization methods; Proportional control; Anticipative Crossover; Gauss-mutation; Genetic Algorithm; Improved Proportional Selection; Real-code;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference, 2008. CCDC 2008. Chinese
  • Conference_Location
    Yantai, Shandong
  • Print_ISBN
    978-1-4244-1733-9
  • Electronic_ISBN
    978-1-4244-1734-6
  • Type

    conf

  • DOI
    10.1109/CCDC.2008.4598058
  • Filename
    4598058