A comprehensive survey: artificial bee colony (ABC) algorithm and applications

• Published in: The Artificial intelligence review Vol. 42; no. 1; pp. 21 - 57
• Main Authors: Karaboga, Dervis, Gorkemli, Beyza, Ozturk, Celal, Karaboga, Nurhan
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.06.2014; Springer Nature B.V
• Subjects: Algorithms; Animal behavior; Artificial Intelligence; Bees; Behavior; Colonies; Computer Science; Expert systems; Fish; Genetic algorithms; Honey; Insects; Intelligence; Marriage; Optimization; Project management; Researchers; Swarm intelligence; Artificial bee colony algorithm; Swarm intelligence; Bee swarm intelligence
• ISSN: 0269-2821; 1573-7462
• DOI: 10.1007/s10462-012-9328-0

Swarm intelligence (SI) is briefly defined as the collective behaviour of decentralized and self-organized swarms. The well known examples for these swarms are bird flocks, fish schools and the colony of social insects such as termites, ants and bees. In 1990s, especially two approaches based on ant colony and on fish schooling/bird flocking introduced have highly attracted the interest of researchers. Although the self-organization features are required by SI are strongly and clearly seen in honey bee colonies, unfortunately the researchers have recently started to be interested in the behaviour of these swarm systems to describe new intelligent approaches, especially from the beginning of 2000s. During a decade, several algorithms have been developed depending on different intelligent behaviours of honey bee swarms. Among those, artificial bee colony (ABC) is the one which has been most widely studied on and applied to solve the real world problems, so far. Day by day the number of researchers being interested in ABC algorithm increases rapidly. This work presents a comprehensive survey of the advances with ABC and its applications. It is hoped that this survey would be very beneficial for the researchers studying on SI, particularly ABC algorithm.