A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm

Authors:
Dervis Karaboga;Bahriye Basturk
Affiliations:
Department of Computer Engineering, Erciyes University, Kayseri, Turkey;Department of Computer Engineering, Erciyes University, Kayseri, Turkey
Venue:
Journal of Global Optimization
Year:
2007

Citing 7
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Abstract

Swarm intelligence is a research branch that models the population of interacting agents or swarms that are able to self-organize. An ant colony, a flock of birds or an immune system is a typical example of a swarm system. Bees' swarming around their hive is another example of swarm intelligence. Artificial Bee Colony (ABC) Algorithm is an optimization algorithm based on the intelligent behaviour of honey bee swarm. In this work, ABC algorithm is used for optimizing multivariable functions and the results produced by ABC, Genetic Algorithm (GA), Particle Swarm Algorithm (PSO) and Particle Swarm Inspired Evolutionary Algorithm (PS-EA) have been compared. The results showed that ABC outperforms the other algorithms.