Overview of research on bee colony algorithms

Abstract

Bee colony algorithms are new swarm intelligence techniques inspired by the intelligent behaviors of real honey bees such as the reproductive behavior and the foraging behavior.More recently,researchers have become very interested in it and its related research.Therefore,this paper preliminary studied the theoretical basis of bee colony algorithms.According to the different bee behaviors,bee colony algorithms were mainly classified into two types,namely the reproductive behavior and the foraging behavior.Then discussed and illustrated the biological mechanism and the most popular algorithm of each type in detail,respectively.Moreover,analyzed and compared genetic algorithm,ant colony optimization,particle swarm optimization and bee colony algorithms in terms of advantages and disadvantages,application fields and performances.Finally,summarized the existing problems in current research on the bee colony algorithms and suggested some future research directions to address the problems.