Open AccessHandling Optimization Problem, and the Scope of Varied Artificial Bee Colony (ABC) Algorithms: A Contemporary
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.f1125.0486s419
Subject(s) - scope (computer science) , artificial bee colony algorithm , relevance (law) , computer science , bees algorithm , process (computing) , optimization algorithm , optimization problem , algorithm , artificial intelligence , operations research , management science , mathematical optimization , metaheuristic , mathematics , engineering , political science , law , programming language , operating system
One of the most successful search algorithms of the last decade is Artificial Bee Colony (ABC) algorithm. It was first coined by Dervis Karaboga, 2005. Since then a group of variants of the algorithm have been anticipated to find solutions for the problems of optimization. The motivation for the algorithm is the search process of honey bees for food sources. The present paper aimed to bring out the evolutionary developments of the algorithm that cover numerous versions of the algorithm with the strategic changes to meet the optimization needs of the adopted problem contexts. This survey clearly reviewed the basic types, advancements, application areas, and the relevance of the ABC algorithm addressing various problem contexts. The efforts made by the research community since the last two decades along with the success stories are discussed in detail. The attachment of the optimization process of ABC with data mining is dealt in particular. Finally the opportunities and the scope of the application of the algorithm in large areas of problem domains are highlighted.