• DocumentCode
    1642831
  • Title

    A fuzzy evolutionary approach to constrained optimisation problems

  • Author

    Van Le, T.

  • Author_Institution
    Fac. of Inf. Sci. & Eng, Univ. of Canberra, ACT, Australia
  • fYear
    1996
  • Firstpage
    274
  • Lastpage
    278
  • Abstract
    Non-linear constrained optimisation problems are fuzzified and a method of fuzzy evolutionary programming is introduced to solve the problems. In this method, the degrees of constraint satisfaction are used as weight factors for the potential solutions. The method is extended to stochastic programming problems and other analogous fuzzy optimisation problems
  • Keywords
    fuzzy logic; genetic algorithms; mathematical programming; nonlinear programming; operations research; stochastic programming; degrees of constraint satisfaction; fuzzy evolutionary approach; fuzzy evolutionary programming; fuzzy optimisation problems; nonlinear constrained optimisation problems; potential solutions; stochastic programming problems; weight factors; Australia; Constraint optimization; Evolutionary computation; Fuzzy sets; Genetic algorithms; Genetic programming; Operations research; Optimization methods; Shape control; Stochastic processes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 1996., Proceedings of IEEE International Conference on
  • Conference_Location
    Nagoya
  • Print_ISBN
    0-7803-2902-3
  • Type

    conf

  • DOI
    10.1109/ICEC.1996.542374
  • Filename
    542374