Artificial bee colony algorithm

INTRODUCTION Nature-inspired computational methodologies and approaches are one of the favorite research topics for both researchers and academic studies in recent years. They're very effective tools for solving complex problems of the real world applications. Most of these algorithms are based on swarm intelligence. Artificial bee colony algorithm is one of the recent and very popular swarm based algorithm mimicking the behavior of the bees. Shortly after introduced, many studies are introduced based on both continuous and discrete optimization problems. The Artificial Bee Colony (ABC) algorithm is a recently introduced optimization algorithm which simulates the foraging behavior of a bee colony which was proposed by Karaboga (2005) for real-parameter optimization. The algorithm is developed by inspecting the behaviors of reel bees on finding nectar amounts and sharing this information of food sources to other bees in their hive. It's one of the swarm-based algorithms like ants, birds and fishes in which individual units perform collective behavior. The aim of this study is to present a bibliographical base to the researchers and enlighten them with ABC algorithm. The main topic of this paper is to give an extensive literature survey of the algorithm and its application areas. In the first section swarm intelligence will be studied. After the properties of swarm intelligence, bee based algorithms will be given. Following this section, artificial bee colony algorithm is briefly described and an extensive literature study is given. Further study notes and conclusion finalize the paper.