Krill herd algorithm with chaotic time interval and elitism scheme

We propose a new chaotic krill herd (CKH) in terms of the recently developed krill herd (KH) algorithm, to solve global numerical optimization problems. In CKH, chaos characteristics are introduced into the KH so as to further enhance its global search ability. The elitism scheme is also applied to store the best krill during the process when updating the krill. This new approach can speed up the global convergence, while preserving the advantage of the standard KH, thus making the approach more feasible for a wider range of practical applications. Here, thirteen different chaotic maps are used to tune the time interval of the krill in the KH algorithm. Twenty-four standard benchmark functions are utilized to verify the effects of the CKH and it has been demonstrated that, in most cases, the performance of CKH with a proper chaotic map is superior to, or at least highly competitive with, the standard KH and other population-based optimization methods. Highlights A new meta-heuristic algorithm, namely CKH is proposed for global optimization. 13 different chaotic maps are applied to tune the main parameter of the KH algorithm. The elitism scheme is applied to keep the best fitness krill. The CKH algorithm is compared with ten well-known methods.