• DocumentCode
    2909508
  • Title

    Improved differential evolution for dynamic optimization problems

  • Author

    Du Plessis, Mathys C. ; Engelbrecht, Andries P.

  • Author_Institution
    Dept. of CS & IS, Nelson Mandela Metropolitan Univ., Port Elizabeth
  • fYear
    2008
  • fDate
    1-6 June 2008
  • Firstpage
    229
  • Lastpage
    234
  • Abstract
    This article reports improvements on DynDE, a approach to using Differential Evolution to solve dynamic optimization problems. Three improvements are suggested, namely favored populations, migrating individuals and a combination of these approaches. The effects of varying the change frequency, peak widths and the number of dimensions of the dynamic environment are investigated. Experimental results are presented that indicate that the suggested approaches constitute considerable improvements on previous research.
  • Keywords
    evolutionary computation; optimisation; differential evolution; dynamic environment; dynamic optimization; Chromium; Clustering algorithms; Evolutionary computation; Frequency; Genetic mutations; Heuristic algorithms; Multidimensional systems; Tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-1822-0
  • Electronic_ISBN
    978-1-4244-1823-7
  • Type

    conf

  • DOI
    10.1109/CEC.2008.4630804
  • Filename
    4630804