• DocumentCode
    2482066
  • Title

    An Improved Artificial Bee Colony Algorithm

  • Author

    Kang, Fei ; Li, Junjie ; Li, Haojin ; Ma, Zhenyue ; Xu, Qing

  • Author_Institution
    Fac. of Infrastruct. Eng., Dalian Univ. of Technol., Dalian, China
  • fYear
    2010
  • fDate
    22-23 May 2010
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Artificial bee colony (ABC) algorithm is one of the most recently proposed swarm intelligence algorithms for global optimization. It performs well in most cases; however, there still exist some problems it cannot solve very well. This paper presents a novel hybrid Hooke Jeeves ABC (HJABC) algorithm with intensification search based on the Hooke Jeeves pattern search and the ABC. The main purpose is to demonstrate how the standard ABC can be improved by incorporating a hybridization strategy. The proposed algorithm is tested on 7 benchmark functions including a wide range of dimensions. Numerical results show that the new algorithm is promising in terms of convergence speed, success rate and solution accuracy.
  • Keywords
    optimisation; search problems; Hooke Jeeves ABC algorithm; Hooke Jeeves pattern search; benchmark functions; global optimization; improved artificial bee colony algorithm; swarm intelligence algorithms; Artificial intelligence; Benchmark testing; Convergence of numerical methods; Particle swarm optimization; Performance analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems and Applications (ISA), 2010 2nd International Workshop on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-5872-1
  • Electronic_ISBN
    978-1-4244-5874-5
  • Type

    conf

  • DOI
    10.1109/IWISA.2010.5473452
  • Filename
    5473452