• DocumentCode
    423900
  • Title

    A novel adaptive genetic algorithms

  • Author

    Liu, De-peng ; Feng, Shu-ting

  • Author_Institution
    Sch. of Sci., Hangzhou Inst. of Electron. Eng., China
  • Volume
    1
  • fYear
    2004
  • fDate
    26-29 Aug. 2004
  • Firstpage
    414
  • Abstract
    This work presents a modified genetic algorithm that is based on the tuning of the mutation probability by the value of individual fitness. The fine modular in current generation is easy to survive in the offspring, and at the same time, the variety of the population is also guaranteed. In the modified scheme, the order of crossover and mutation is changed in order to avoid the repetition in the computation of individual fitness. Simulation result have shown that the modified scheme is prior to the GAs commonly used.
  • Keywords
    genetic algorithms; probability; adaptive genetic algorithm; individual fitness; mutation probability; Algebra; Algorithm design and analysis; Cybernetics; Genetic algorithms; Genetic mutations; Least squares methods; Optimization methods; Registers; Turning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
  • Print_ISBN
    0-7803-8403-2
  • Type

    conf

  • DOI
    10.1109/ICMLC.2004.1380721
  • Filename
    1380721