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Zbl 1204.65074
Zhu, Guopu; Kwong, Sam
Gbest-guided artificial bee colony algorithm for numerical function optimization. (English)
[J] Appl. Math. Comput. 217, No. 7, 3166-3173 (2010). ISSN 0096-3003

Summary: The artificial bee colony (ABC) algorithm invented recently by {\it D. Karaboga} [Erciyes University, Kayseri, Turkey, Technical Report-TR06 (2005)] is a biological-inspired optimization algorithm, which has been shown to be competitive with some conventional biological-inspired algorithms, such as genetic algorithm (GA), differential evolution (DE) and particle swarm optimization (PSO). However, there is still an insufficiency in the ABC algorithm regarding its solution search equation, which is good at exploration but poor at exploitation. Inspired by PSO, we propose an improved ABC algorithm called gbest-guided ABC (GABC) algorithm by incorporating the information of the global best (gbest) solution into the solution search equation to improve the exploitation. Experimental results obtained on a set of numerical benchmark functions show that GABC algorithm can outperform the ABC algorithm in most of them.

MSC 2000:: *65K05 Mathematical programming (numerical methods)

Keywords: artificial bee colony algorithm; genetic algorithm; particle swarm optimization; differential evolution; biological-inspired optimization algorithm; numerical function optimization

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Zentralblatt MATH Berlin [Germany]