• DocumentCode
    719116
  • Title

    A new distributed differential evolution algorithm

  • Author

    Khaparde, A.R. ; Raghuwanshi, M.M. ; Malik, L.G.

  • Author_Institution
    Comput. Sci. & Eng., GHRCE, Nagpur, India
  • fYear
    2015
  • fDate
    15-16 May 2015
  • Firstpage
    558
  • Lastpage
    562
  • Abstract
    A new differential evolutionary algorithm with species and best vector selection (DESBS) has been proposed. It uses best determination method (BDM) to determine the best members in population. Each best member is considered as a niche in population. The species formation takes place around these niches. Once the species get formed then the standard differential evolution algorithm (SDE) has been used. If species is not performing well, then the merging to the nearby species takes place. The scale up study of various parameters of DESBS is done to get best parameter setting. The performance of newly proposed algorithm is tested on uni-modal and multi-modal test functions. It got success in solving wide range of problems. The results are compared with standard Differential evolution algorithm (SDE) and other state-of-art algorithms. The results are encouraging one.
  • Keywords
    evolutionary computation; BDM; DESBS; SDE; best determination method; differential evolutionary algorithm with species and best vector selection; distributed differential evolution algorithm; multimodal test function; standard differential evolution algorithm; unimodal test function; Algorithm design and analysis; Evolution (biology); Evolutionary computation; Merging; Sociology; Standards; Statistics; formatting; insert; style; styling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computing, Communication & Automation (ICCCA), 2015 International Conference on
  • Conference_Location
    Noida
  • Print_ISBN
    978-1-4799-8889-1
  • Type

    conf

  • DOI
    10.1109/CCAA.2015.7148456
  • Filename
    7148456