• DocumentCode
    1687719
  • Title

    Simulated annealing artificial fish swarm algorithm

  • Author

    Jiang, Mingyan ; Cheng, Yongming

  • Author_Institution
    Sch. of Inf. Sci. & Eng., Shandong Univ., Jinan, China
  • fYear
    2010
  • Firstpage
    1590
  • Lastpage
    1593
  • Abstract
    This paper presents a novel stochastic approach called the simulated annealing-artificial fish swarm algorithm (SA-AFSA) for solving some multimodal problems. The proposed algorithm incorporates the simulated annealing (SA) into artificial fish swarm algorithm (AFSA) to improve the performance of the AFSA. The hybrid algorithm has the following features: the hybrid algorithm maintains 1) the strong local searching ability of the SA and 2) the swarm intelligence of AFSA. The experimental results indicate that in all the test cases, the SA-AFSA can obtain much better optimization precision and the convergence speed compared with AFSA.
  • Keywords
    simulated annealing; artificial fish swarm algorithm; convergence speed; multimodal problems; optimization precision; simulated annealing; Algorithm design and analysis; Clustering algorithms; Marine animals; Particle swarm optimization; Signal processing algorithms; Simulated annealing; artificial fish swarm algorithm; data clustering; multimodal problem; simulated annealing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation (WCICA), 2010 8th World Congress on
  • Conference_Location
    Jinan
  • Print_ISBN
    978-1-4244-6712-9
  • Type

    conf

  • DOI
    10.1109/WCICA.2010.5554452
  • Filename
    5554452