• DocumentCode
    1899424
  • Title

    Immune-Difference Algorithm

  • Author

    Fu, Xuan ; Liu, Hao ; Fan, Yaoqun ; Zhao, Xinchao

  • Author_Institution
    Sch. of Sci., Beijing Univ. of Posts & Telecommun., Beijing, China
  • Volume
    2
  • fYear
    2012
  • fDate
    23-25 March 2012
  • Firstpage
    406
  • Lastpage
    409
  • Abstract
    This paper introduces difference mutation idea for diversified search to elitist search-based immune optimization algorithm for function optimization. The idea of difference mutation is merged into the process of clonal selection and hupermutation algorithm, so that the new solutions have the tendency to get close to the global optimal solution. The introduction of differential algorithm idea greatly accelerates the convergence speed and makes the search algorithm produces better performance under a fixed number of steps. In short, the performance of the immune algorithm is greatly improved by introduction of differential algorithm.
  • Keywords
    artificial immune systems; convergence; search problems; clonal selection; convergence speed; difference mutation; differential algorithm; elitist search-based immune optimization algorithm; function optimization; global optimal solution; hupermutation algorithm; immune-difference algorithm; search algorithm; Arrays; Cloning; Convergence; Educational institutions; Immune system; Optimization; Software algorithms; Clonal Selection; Difference algorithm; Hypermutation; Immune algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Electronics Engineering (ICCSEE), 2012 International Conference on
  • Conference_Location
    Hangzhou
  • Print_ISBN
    978-1-4673-0689-8
  • Type

    conf

  • DOI
    10.1109/ICCSEE.2012.40
  • Filename
    6188050