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
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;
Conference_Titel :
Computational Intelligence and Design (ISCID), 2012 Fifth International Symposium on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4673-2646-9
DOI :
10.1109/ISCID.2012.191