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.
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References in zbMATH (referenced in 289 articles )
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- Al-Salamah, Muhammad: Economic production quantity with the presence of imperfect quality and random machine breakdown and repair based on the artificial bee colony heuristic (2018)
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- Dunder, Emre; Gumustekin, Serpil; Cengiz, Mehmet Ali: Variable selection in gamma regression models via artificial bee colony algorithm (2018)
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- García Nieto, P. J.; García-Gonzalo, E.; Álvarez Antón, J. C.; González Suárez, V. M.; Mayo Bayón, R.; Mateos Martín, F.: A comparison of several machine learning techniques for the centerline segregation prediction in continuous cast steel slabs and evaluation of its performance (2018)
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- Jin, Ye; Sun, Yuehong; Ma, Hongjiao: A developed artificial bee colony algorithm based on cloud model (2018)
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Further publications can be found at: http://mf.erciyes.edu.tr/abc/publ.htm