A systematic review of applications of Bee Colony Optimization

In this paper an overview of Bee Colony Optimization and area of its application where it has been used is given. Bee Colony Optimization is based on concept of Swarm Intelligence (SI), the artificial intelligence (AI) which is based on decentralized and self-organizing systems that can either be natural or artificial. Bee Colony Optimization is a meta-heuristic algorithm which uses the swarm behavior of bees to interact locally with one another in their environment that simulates the foraging behavior of honey bees and combines the global explorative search with local explorative search. The Bees Algorithms hunts synchronously the most promising regions of the solution space and also samples the most favorable regions. BCO is a class of optimization algorithm which uses the bottom-up approach of modeling and swarm intelligence of honeybees. The primary aim of this paper is to give an insight into the areas in which BCO can be used.