• DocumentCode
    2845473
  • Title

    Genetic Ant Algorithm for Continuous Function Optimization and Its MATLAB Implementation

  • Author

    Li, Yan ; Chen, Yuanyi

  • Author_Institution
    Coll. of Mech. & Electr. Eng., Central South Univ., Changsha, China
  • Volume
    1
  • fYear
    2010
  • fDate
    13-14 Oct. 2010
  • Firstpage
    791
  • Lastpage
    794
  • Abstract
    Due to low accuracy of genetic algorithm and slow speed of ant algorithm for solving the problem, a hybrid algorithm based on genetic algorithm and ant algorithm is promoted and its MATLAB implementation is introduced in this paper. Using the hybrid algorithm to solve the problems of continuous function optimization, the results show that the hybrid algorithm has faster convergence and better optimization performance than genetic algorithm and ant algorithm.
  • Keywords
    genetic algorithms; mathematics computing; Matlab implementation; ant algorithm; continuous function optimization; genetic algorithm; Algorithm design and analysis; Cities and towns; Genetic algorithms; Genetics; MATLAB; Optimization; Probability; MATLAB; algorithm programming; continuous function; genetic ant algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent System Design and Engineering Application (ISDEA), 2010 International Conference on
  • Conference_Location
    Changsha
  • Print_ISBN
    978-1-4244-8333-4
  • Type

    conf

  • DOI
    10.1109/ISDEA.2010.135
  • Filename
    5743298
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2845473