• DocumentCode
    588736
  • Title

    Linear Weighted Gbest-Guided Artificial Bee Colony Algorithm

  • Author

    Yanyu Zhang ; Peng Zeng ; Yang Wang ; Baohui Zhu ; Fangjun Kuang

  • Author_Institution
    Shenyang Inst. of Autom., Shenyang, China
  • Volume
    2
  • fYear
    2012
  • fDate
    28-29 Oct. 2012
  • Firstpage
    155
  • Lastpage
    159
  • Abstract
    Artificial bee colony (ABC) algorithm invented recently by Karaboga is a competitive stochastic population-based optimization algorithm. However, solution search equation used in the original ABC algorithm is good at exploration but poor at exploitation. an improved ABC algorithm called Gbest-guided ABC (GABC) was introduced by researchers to improve the exploitation of ABC algorithm. in order to improve the GABC algorithm further, we propose an improved GABC algorithm with a linear weight called WGABC, and introduce a novel solution search equation used at scout bee stage of WGABC algorithm. Experimental results tested on a set of numerical benchmark functions show that WGABC can outperform ABC and GABC algorithms in most of the experiments.
  • Keywords
    stochastic programming; swarm intelligence; WGABC algorithm; competitive stochastic population-based optimization algorithm; linear weighted Gbest-guided artificial bee colony algorithm; numerical benchmark functions; scout bee stage; solution search equation; Benchmark testing; Classification algorithms; Educational institutions; Equations; Optimization; Particle swarm optimization; Signal processing algorithms; Artificial bee colony algorithm; Biological-inspired optimization algorithm; Numerical function optimization; Swarm intelligence;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Design (ISCID), 2012 Fifth International Symposium on
  • Conference_Location
    Hangzhou
  • Print_ISBN
    978-1-4673-2646-9
  • Type

    conf

  • DOI
    10.1109/ISCID.2012.191
  • Filename
    6405590