期刊名称：International Journal of Computer Science and Information Technologies
电子版ISSN：0975-9646
出版年度：2014
卷号：5
期号：4
页码：5651-5658
出版社：TechScience Publications
摘要：Artificial Bee Colony Algorithm (ABC) is the most recent advance technique to solve many mathematical problems and engineering problems. The inspiration behind this is Nature, where problems are solved on the basis of behaviour of swarms, ants, bees etc. The foraging behaviour of honey bees plays an important role while approaching ABC algorithms. This paper introduces a new hybrid approach to enhance the performance of original ABC algorithm. In this a composition algorithm is introduced where Best-so-far ABC and Golden section search algorithms are hybrid together to improve the success rate of ABC algorithm. Best-so-far was modified version of Original ABC where exploitation and exploration both process were modified, and in golden section search a function can be optimized in a given range with the a parameter called as golden ratio. The proposed algorithm is named as BSFMeABC i.e. Best-so-far based on memetic search. This algorithm is tested over some benchmark functions and some well known engineering problems. On the basis of feature like success rate, mean function evaluation, acceptable error etc. a comparison chart is made which show the performance evaluation of these algorithms
