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Zbl 1169.65053
Karaboga, Dervis; Akay, Bahriye
A comparative study of artificial bee colony algorithm. (English)
[J] Appl. Math. Comput. 214, No. 1, 108-132 (2009). ISSN 0096-3003

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.

MSC 2000:: *65K05 Mathematical programming (numerical methods)
90C15 Stochastic programming

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

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Zentralblatt MATH Berlin [Germany]