A REVIEW ON ARTIFICIAL BEE COLONY AND ITS ENGINEERING APPLICATIONS
Abhishek Sharma, Abhinav Sharma, Sachi Choudhary, Rupendra Kumar Pachauri, Aayush Shrivastava, Deepak Kumar
Abstract
Swarm intelligence (SI) is unique and best-known area of research. For computer scientists, engineers, economists, bioinformatician, functional researchers, and several other disciplines, SI is becoming an increasingly important research area. It is abruptly characterized as the decentralized and self-organized swarms ' collective behaviour. The swarm's intelligence lies in the communication networks between both basic agents as well as between agents and the world. Bird flocks, fish schools and the colony of social insects such as termites, ants and bees are the well-known examples for these swarms. Although SI requires the features of self-organization to be strongly and this characteristics is clearly depicted by honey bee colonies, the researchers have spent the past few years to implement the behaviour of these swarm systems to describe new intelligent techniques, especially from the early 2000s. Different researchers have proposed a large number of swarm-based algorithms in recent years. Artificial Bee Colony (ABC) algorithm is one of Karaboga's most known stochastic, swarm-based metaheuristicalgorithm anticipated in 2005 inspired by honeybees ' foraging behaviour. Because of its simple characteristics, smooth to implement and less control parameters, ABC algorithm has gained extensive admiration between scholars in a short span of time. It is an optimization method that incorporates a population-based searching process in which artificial bees adjust their food positions over time. Where, the main objective of the bees is to detect the location of food source with better nectar quantity and ultimately the food source with the better nectar. If the nectar quantity of new source is better than that found in memory, the bees recite the current position and neglect the previous one. This chapter provides the comprehensive review of ABC algorithm with its applications to solve the various complex engineering problems. The different version i.e. modified, and hybrid of ABC algorithm are presented and discussed. The chapter also presents the scope of future work