• DocumentCode
    1197670
  • Title

    A stop criterion to accelerate magnetic optimization process using genetic algorithms and finite element analysis

  • Author

    Hajji, Omessad ; Brisset, Stéphane ; Brochet, Pascal

  • Author_Institution
    Ecole Centrale de Lille, Villeneuve d´´Ascq, France
  • Volume
    39
  • Issue
    3
  • fYear
    2003
  • fDate
    5/1/2003 12:00:00 AM
  • Firstpage
    1297
  • Lastpage
    1300
  • Abstract
    In this paper, a new stop criterion is proposed for genetic algorithms using a response surface fitted on the best individuals. This criterion is tested on a superconducting magnetic energy storage optimization and compared with stop criteria found in the literature that are reviewed and detailed.
  • Keywords
    finite element analysis; genetic algorithms; response surface methodology; superconducting magnet energy storage; finite element analysis; genetic algorithm; magnetic device; optimization; response surface methodology; stop criterion; superconducting magnetic energy storage; Acceleration; Algorithm design and analysis; Convergence; Finite element methods; Genetic algorithms; Magnetic analysis; Magnetic devices; Response surface methodology; Superconducting magnetic energy storage; Testing;
  • fLanguage
    English
  • Journal_Title
    Magnetics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9464
  • Type

    jour

  • DOI
    10.1109/TMAG.2003.810209
  • Filename
    1198458