• DocumentCode
    1951156
  • Title

    A new genetic algorithm for nonlinear programming problems

  • Author

    Jiafu Tang ; Dingwei Wang

  • Author_Institution
    Sch. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
  • Volume
    5
  • fYear
    1997
  • fDate
    12-12 Dec. 1997
  • Firstpage
    4906
  • Abstract
    A special genetic algorithm with mutation along the weighted gradient direction for nonlinear programming problems is proposed. It uses penalty function to construct fitness function for evaluating the solution which violates the constraints. The convergence analysis of the method are also given in this paper.
  • Keywords
    convergence of numerical methods; genetic algorithms; nonlinear programming; convergence; fitness function; genetic algorithm; nonlinear programming; penalty function; weighted gradient direction; Algorithm design and analysis; Constraint optimization; Decoding; Functional programming; Genetic algorithms; Genetic engineering; Genetic mutations; Information science; Optimization methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 1997., Proceedings of the 36th IEEE Conference on
  • Conference_Location
    San Diego, CA, USA
  • ISSN
    0191-2216
  • Print_ISBN
    0-7803-4187-2
  • Type

    conf

  • DOI
    10.1109/CDC.1997.649813
  • Filename
    649813
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1951156