Chaotic elephant herding optimization algorithm

Abstract

Swarm intelligence algorithms represent stochastic optimization algorithms that proved to be powerful for finding suboptimal solutions for hard optimization problems. Elephant herding optimization algorithm is a rather new and promising representative of that class of optimization algorithms that has already been used in numerous applications. In recent years, chaotic maps were incorporated into the swarm intelligence algorithms in order to improve the search quality. In this paper we introduced two different chaotic maps into the original elephant herding optimization algorithm. The proposed methods were tested on 15 benchmark functions from CEC 2013. Obtained results were compared to the regular elephant herding optimization algorithm as well to the particle swarm optimization. Test results proved that the proposed chaotic elephant herding optimization algorithm has better performance and obtained better results.