• DocumentCode
    3576126
  • Title

    Improved genetic algorithm to enhance the ability of local search

  • Author

    Chen Yuan

  • Author_Institution
    Wuhan Univ. of Sci. & Technol. City Coll., Wuhan, China
  • fYear
    2014
  • Firstpage
    2100
  • Lastpage
    2103
  • Abstract
    We proposed an improved genetic algorithm (GA) based on floating-point encoding, and greatly enhanced its local adjustment capability using linear crossover operator, dynamic mutation operator, and the substitution and retention strategies used at different population evolutionary stages. Numerical simulation further validated the effectiveness of the improved GA.
  • Keywords
    genetic algorithms; search problems; GA; dynamic mutation operator; floating-point encoding; improved genetic algorithm; linear crossover operator; local search; numerical simulation; population evolutionary stages; retention strategy; substitution strategy; Biological cells; Encoding; Genetic algorithms; Genetics; Optimization; Sociology; Statistics; Approximate optimal solution; Binary encoding; Floatingpoint encoding; Genetic algorithm; Global optimal solution;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mechatronics and Control (ICMC), 2014 International Conference on
  • Print_ISBN
    978-1-4799-2537-7
  • Type

    conf

  • DOI
    10.1109/ICMC.2014.7231936
  • Filename
    7231936
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3576126