• DocumentCode
    1634327
  • Title

    Free Search Differential Evolution

  • Author

    Omran, Mahamed G H ; Engelbrecht, Andries P.

  • Author_Institution
    Dept. of Comput. Sci., Gulf Univ. for Sci. & Technol., Mishref
  • fYear
    2009
  • Firstpage
    110
  • Lastpage
    117
  • Abstract
    Free search differential evolution (FSDE) is a new, population-based meta-heuristic algorithm that is a hybrid of concepts from free search (FS), differential evolution (DE) and opposition-based learning. The performance of the proposed approach is investigated and compared with DE and one of the recent variants of DE when applied to ten benchmark functions. The experiments conducted show that FSDE provides excellent results with the added advantage of no parameter tuning.
  • Keywords
    learning (artificial intelligence); optimisation; search problems; stochastic processes; free search differential evolution; opposition-based learning; population-based metaheuristic algorithm; Africa; Animals; Computer science; Design engineering; Design optimization; Image processing; Optimization methods; Pattern recognition; Space technology; Stochastic resonance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2009. CEC '09. IEEE Congress on
  • Conference_Location
    Trondheim
  • Print_ISBN
    978-1-4244-2958-5
  • Electronic_ISBN
    978-1-4244-2959-2
  • Type

    conf

  • DOI
    10.1109/CEC.2009.4982937
  • Filename
    4982937
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1634327