Representative artificial bee colony algorithms: A survey

Abstract

Artificial bee colony algorithm (ABC) is a relatively new optimization technique which has been shown to be competitive to other population-based algorithms. It shows more effective than genetic algorithm (GA), particle swarm optimization (PWO), and ant colony algorithm (ACO). However, ABC is good at exploration but poor at exploitation, and its convergence speed is also an issue in some cases. For these insufficiencies, researchers have proposed some modified algorithms. This paper describes ABC, the modified ABC, the improved ABC, the best-so-far ABC, the ACO-ABC algorithm with hadoop that our team has designed and the applications of artificial bee colony algorithm, especially in the cloud computing. Finally, the future research aspects of the swarm intelligence are emphatically suggested, especially the broad-applied bee colony algorithms. © Springer-Verlag Berlin Heidelberg 2013.