• DocumentCode
    3380658
  • Title

    A dynamic mutation genetic algorithm

  • Author

    Hong, Tzung-Pei ; Wang, Hong-Shung

  • Author_Institution
    Dept. of Inf. Manage, Kaohsiung Polytech. Inst., Taiwan
  • Volume
    3
  • fYear
    1996
  • fDate
    14-17 Oct 1996
  • Firstpage
    2000
  • Abstract
    Conventional genetic algorithms use only one mutation operator to generate the next generation. Determining which mutation operator should be used is quite difficult and is usually done by trial-and-error. In this paper, a new genetic algorithm, the dynamic mutation genetic algorithm (DMGA), is proposed to solve the problem. The dynamic mutation genetic algorithm uses more than one mutation operator to generate the next generation. The mutation ratio of each operator changes along with the evaluation results from the respective offspring in the next generation. We thus expect that really good operators will have an increased effect on the genetic process
  • Keywords
    genetic algorithms; dynamic mutation genetic algorithm; genetic process; mutation ratio; Automatic control; Electrical capacitance tomography; Fuzzy logic; Genetic algorithms; Genetic mutations; Information management; Machine learning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics, 1996., IEEE International Conference on
  • Conference_Location
    Beijing
  • ISSN
    1062-922X
  • Print_ISBN
    0-7803-3280-6
  • Type

    conf

  • DOI
    10.1109/ICSMC.1996.565436
  • Filename
    565436