Research Area:  Metaheuristic Computing

Abstract:

Krill herd (KH) is a novel swarm-based metaheuristic optimization algorithm inspired by the krill herding behavior. The objective function in the KH optimization process is based on the least distance between the food location and position of a krill. The KH method has been proven to outperform several state-of-the-art metaheuristic algorithms on many benchmarks and engineering cases. This paper presents a comprehensive review of different versions of the KH algorithm and their engineering applications. The study is divided into the following general parts: KH variants, engineering optimization/application, and theoretical analysis. In addition, specific features of KH and future directions are discussed.

Keywords:  
Krill herd
swarm-based
metaheuristic
optimization algorithm
food location
benchmarks
engineering cases

Author(s) Name:  Gai-Ge Wang, Amir H. Gandomi, Amir H. Alavi & Dunwei Gong

Publisher name:  Springer

DOI:  10.1007/s10462-017-9559-1

Volume Information:  51, pages 119–148

Paper Link:   https://link.springer.com/article/10.1007/s10462-017-9559-1