• DocumentCode
    3148607
  • Title

    The enhanced genetic algorithms for the optimization design

  • Author

    Guo, Pengfei ; Wang, Xuezhi ; Han, Yingshi

  • Author_Institution
    Sch. of Civil & Archit. Eng., Liaoning Univ. of Technol., Jinzhou, China
  • Volume
    7
  • fYear
    2010
  • fDate
    16-18 Oct. 2010
  • Firstpage
    2990
  • Lastpage
    2994
  • Abstract
    Three different kinds of the novel enhanced genetic algorithm procedures including the hybrid genetic algorithm, interval genetic algorithm and hybrid interval genetic algorithm are respectively presented. As the results of the proven systems show, the hybrid genetic algorithm can determines the better optimum design than the traditional optimization algorithms and genetic algorithm. The interval genetic algorithm and hybrid interval genetic algorithm can avoid calculating system slope in traditional interval analysis and determines the optimum interval range of the parameters under allowable corresponding objective error boundary. It is the first time that genetic algorithm has been applied to interval optimization process.
  • Keywords
    genetic algorithms; hybrid interval genetic algorithm; interval analysis; interval genetic algorithm; interval optimization process; optimization design; optimum interval range; Algorithm design and analysis; Biological cells; Gallium; Genetic algorithms; Genetics; Optimization; Polynomials; genetic algorithms; hybrid genetic algorithm; hybrid interval genetic algorithm; interval genetic algorithm; optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Engineering and Informatics (BMEI), 2010 3rd International Conference on
  • Conference_Location
    Yantai
  • Print_ISBN
    978-1-4244-6495-1
  • Type

    conf

  • DOI
    10.1109/BMEI.2010.5639829
  • Filename
    5639829