1Research Scholar, Department of Computer Science & IT, Jagannath University, Jaipur. Email: sandeep.kumar@jagannathuniversity.org
2Assistant Professor, Department of Mathematics, Jagannath University, Jaipur. Email: vivek.sharma@jagannathuniversity.org
3Research Scholar, Department of Computer Science & IT, Jagannath University, Jaipur. Email: rajanikpoonia@gmail.com
Online published on 22 June, 2017.
Artificial bee colony (ABC) algorithm is a well known and one of the latest swarm intelligence based techniques. This method is a population based meta-heuristic algorithm used for numerical optimization. It is based on the intelligent behavior of honey bees. Artificial Bee Colony algorithm is one of the most popular techniques that are used in optimization problems. Artificial Bee Colony algorithm has some major advantages over other heuristic methods. To utilize its good feature a number of researchers combined ABC algorithm with other methods, and generate some new hybrid methods. This paper provides comparative analysis of hybrid differential Artificial Bee Colony algorithm with hybrid ABC-SPSO, Genetic algorithm and Independent rough set approach based on some parameters like technique, dimension, methodology etc.
Optimization techniques, Nature inspired techniques, Artificial Bee Colony algorithm, DE, Genetic Algorithm, Rough Set, PSO
