ABC

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


References in zbMATH (referenced in 289 articles )

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  1. Zou, Wenping; Zhu, Yunlong; Chen, Hanning; Sui, Xin: A clustering approach using cooperative artificial bee colony algorithm (2010)
  2. Ahrari, A.; Shariat-Panahi, M.; Atai, A. A.: GEM: A novel evolutionary optimization method with improved neighborhood search (2009)
  3. Karaboga, Dervis; Akay, Bahriye: A comparative study of artificial bee colony algorithm (2009)
  4. Karaboga, Dervis; Akay, Bahriye: A survey: algorithms simulating bee swarm intelligence (2009) ioport
  5. Karaboga, Nurhan: A new design method based on artificial bee colony algorithm for digital IIR filters (2009)
  6. Subbotina, S. A.; Oleinik, Al. A.: Multiagent optimization based on the bee-colony method (2009)
  7. Karaboga, Dervis; Basturk, Bahriye: On the performance of artificial bee colony (ABC) algorithm. (2008) ioport
  8. Karaboga, Dervis; Basturk, Bahriye: A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm (2007)
  9. Karaboga, Dervis; Basturk, Bahriye: Artificial bee colony (ABC) optimization algorithm for solving constrained optimization problems (2007) ioport

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Further publications can be found at: http://mf.erciyes.edu.tr/abc/publ.htm