• DocumentCode
    1541773
  • Title

    A few results for using genetic algorithms in the design of electrical machines

  • Author

    Wurtz, F. ; Richomme, M. ; Bigeon, J. ; Sabonnadiere, J.C.

  • Author_Institution
    Lab. d´´Electrotech. de Grenoble, CNRS, St. Martin d´´Heres, France
  • Volume
    33
  • Issue
    2
  • fYear
    1997
  • fDate
    3/1/1997 12:00:00 AM
  • Firstpage
    1892
  • Lastpage
    1895
  • Abstract
    Genetic algorithms (GAs) seem to be attractive for the design of electrical machines but their main difficulty is in finding a configuration so that they are efficient. This paper exposes a criterion and a methodology which the authors have developed in order to find efficient configurations. The first configuration they obtained is then detailed. The results based on this configuration are detailed, together with an example of a design problem
  • Keywords
    design engineering; electric machines; genetic algorithms; machine theory; criterion; efficient configurations; electrical machine design; genetic algorithms; methodology; Algorithm design and analysis; Biological information theory; Constraint optimization; Design optimization; Encoding; Genetic algorithms; Genetic mutations; Optimal control; Probability; Testing;
  • fLanguage
    English
  • Journal_Title
    Magnetics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9464
  • Type

    jour

  • DOI
    10.1109/20.582656
  • Filename
    582656