• DocumentCode
    3317340
  • Title

    An Improved Immune Genetic Algorithm Based on Niche Algorithm and Its Application

  • Author

    Dong, Lili ; Xue, Chaogai ; Li, Guohua

  • Author_Institution
    Sch. of Manage. Eng., Zhengzhou Univ., Zhengzhou, China
  • fYear
    2010
  • fDate
    23-25 July 2010
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    In order to overcome traditional genetic algorithm (GA)\´s deficiency of slow convergence, and Niche algorithm\´s too fast convergence, this paper presents a new Improved Immune Genetic Algorithm (IIGA) based on the improved Niche algorithm. Firstly, the improved Niche algorithm, including convergence function, and "noise" chromosome, is given. Then based on the proposed flowchart of IIGA, the steps of the algorithm are introduced in detail. Finally, the IIGA is exemplified, and proved to be feasible and effective by comparing with self-adaptive Genetic Algorithm(SAGA) and traditional GA.
  • Keywords
    convergence; genetic algorithms; convergence function; improved immune genetic algorithm; niche algorithm; noise chromosome; Acceleration; Biological cells; Chaos; Convergence; Engineering management; Flowcharts; Genetic algorithms; Genetic engineering; Immune system; Scheduling algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Engineering and Electronic Commerce (IEEC), 2010 2nd International Symposium on
  • Conference_Location
    Ternopil
  • Print_ISBN
    978-1-4244-6972-7
  • Electronic_ISBN
    978-1-4244-6974-1
  • Type

    conf

  • DOI
    10.1109/IEEC.2010.5533280
  • Filename
    5533280