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Karaboga, Dervis; Akay, Bahriye

A comparative study of artificial bee colony algorithm. (English) Zbl 1169.65053

Appl. Math. Comput. 214, No. 1, 108-132 (2009).
Summary: The artificial bee colony (ABC) algorithm is one of the most recently introduced swarm-based algorithms. ABC simulates the intelligent foraging behaviour of a honeybee swarm. In this work, ABC is used for optimizing a large set of numerical test functions and the results produced by ABC algorithm are compared with the results obtained by genetic algorithm, particle swarm optimization algorithm, differential evolution algorithm and evolution strategies. Results show that the performance of the ABC is better than or similar to those of other population-based algorithms with the advantage of employing fewer control parameters.

Cited in 135 Documents

MSC:

65K05 Numerical mathematical programming methods
90C15 Stochastic programming

Keywords:

swarm intelligence; evolution strategies; genetic algorithms; differential evolution; particle swarm optimization; artificial bee colony algorithm; unconstrained optimization; numerical examples

Software:

CIXL2; Genocop; ABC
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\textit{D. Karaboga} and \textit{B. Akay}, Appl. Math. Comput. 214, No. 1, 108--132 (2009; Zbl 1169.65053)
Full Text: DOI

References:

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