• DocumentCode
    3338204
  • Title

    A Self-Organization Genetic Algorithm with Cycle Mutation

  • Author

    Wang, Na ; Zhuang, Jian ; Du, Haifeng ; Wang, Sun An

  • Author_Institution
    Sch. of Mech. Eng., Xi´´an Jiaotong Univ., Xi´´an
  • Volume
    2
  • fYear
    2008
  • fDate
    3-5 Nov. 2008
  • Firstpage
    530
  • Lastpage
    533
  • Abstract
    In this paper, a mutation with cycle probability is designed by simulating the evolutionary rule of the earth creature, and a genetic algorithm based on the cycle mutation, presents the ability in improving search efficiency and overcoming premature to some extent. To further improve performance of the algorithm, the selection is mended according to the phenomena that optimum individual always plays a major role, and an improved cycle mutation genetic algorithm is proposed. The experiment results on the benchmark functions optimization show that exploration and exploitation of this algorithm is better than some well-known evolution algorithms and it is not sensitive to the initial population distribution.
  • Keywords
    genetic algorithms; probability; search problems; cycle mutation probability; earth creature; evolutionary rule; search problem; self-organization genetic algorithm; Artificial intelligence; Computational efficiency; Evolution (biology); Genetic algorithms; Genetic mutations; Mechanical engineering; Public policy; Scheduling algorithm; Size control; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Tools with Artificial Intelligence, 2008. ICTAI '08. 20th IEEE International Conference on
  • Conference_Location
    Dayton, OH
  • ISSN
    1082-3409
  • Print_ISBN
    978-0-7695-3440-4
  • Type

    conf

  • DOI
    10.1109/ICTAI.2008.30
  • Filename
    4669820