This paper reviews a list of krill herd (KH)-style algorithms and the associated variants. As a general overview of this algorithm, the paper presents a systematic approach for cataloguing and classifying the algorithms into three areas: improved, hybrid, and variant. The KH algorithm is a relatively new bio-inspired optimization algorithm, with many variations that have been developed to address specific problem areas. KH is a swarm-based metaheuristic algorithm, which is a problem independent technique that does not address a specific issue, but utilizes a range of parameters to derive a solution. The concept of this algorithm is based on the simulation of krill herding behavior. The objective function used in KH is determined by the least distance to food and the highest density of the herd population.

The paper is comprehensive and leaves the reader overwhelmed by the sheer number of variations and techniques. The explanations and definitions of each type require further investigation to fully understand the details and finer concepts. However, while this paper is not for the layperson, it would be of interest to those academics and researchers who seek a comprehensive review of KH algorithms.