• DocumentCode
    954087
  • Title

    A novel algorithm for multimodal function optimization based on evolution strategy

  • Author

    Im, Chang-Hwan ; Kim, Hong-Kyu ; Jung, Hyun-Kyo ; Choi, Kyung

  • Author_Institution
    Sch. of Electr. Eng., Seoul Nat. Univ., South Korea
  • Volume
    40
  • Issue
    2
  • fYear
    2004
  • fDate
    3/1/2004 12:00:00 AM
  • Firstpage
    1224
  • Lastpage
    1227
  • Abstract
    In this paper, a novel algorithm for multimodal function optimization is proposed, based on the concept of evolution strategy. A new concept, named restricted evolution, shows more improved characteristics than conventional approaches that have been used for multimodal function optimization. The efficiency and usefulness of the proposed method will be verified by the application to various cases including practical optimization problems.
  • Keywords
    evolutionary computation; function approximation; evolution strategy; multimodal function optimization; optimization problems; restricted evolution; Algorithm design and analysis; Clustering algorithms; Convergence; Genetic algorithms; Heuristic algorithms; Optimization methods; Shape; Simulated annealing;
  • fLanguage
    English
  • Journal_Title
    Magnetics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9464
  • Type

    jour

  • DOI
    10.1109/TMAG.2004.824805
  • Filename
    1284640
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=954087