• DocumentCode
    460796
  • Title

    Fully Informed Differential Evolution

  • Author

    Omran, Mahamed G H ; Engelbrecht, Andries P. ; Salman, Ayed ; Hamdan, Suha A.

  • Author_Institution
    Dept. of Comput. Sci., Gulf Univ. for Sci. & Technol.
  • Volume
    1
  • fYear
    2006
  • fDate
    Nov. 2006
  • Firstpage
    278
  • Lastpage
    281
  • Abstract
    Differential evolution (DE) is generally considered as a reliable, accurate, robust and fast optimization technique. DE has been successfully applied to solve a wide range of numerical optimization problems. A fully informed DE (FIDE) is proposed in this paper where each member of the individual´s neighborhood contributes to the new mutant vector. The performance of FIDE is investigated and compared with other versions of DE. The experiments conducted show that FIDE generally outperformed the other DE versions in all the benchmark functions
  • Keywords
    evolutionary computation; vectors; benchmark function; fully informed differential evolution; mutant vector; numerical optimization; Birds; Computer science; Genetic mutations; Neodymium; Particle swarm optimization; Probability distribution; Reliability engineering; Robustness; Stochastic processes; Topology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Security, 2006 International Conference on
  • Conference_Location
    Guangzhou
  • Print_ISBN
    1-4244-0605-6
  • Electronic_ISBN
    1-4244-0605-6
  • Type

    conf

  • DOI
    10.1109/ICCIAS.2006.294137
  • Filename
    4072090
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=460796