Research Area:  Metaheuristic Computing

Abstract:

Elephant herding optimization (EHO) is a nature-inspired metaheuristic optimization algorithm based on the herding behavior of elephants. EHO uses a clan operator to update the distance of the elephants in each clan with respect to the position of a matriarch elephant. The superiority of the EHO method to several state-of-the-art metaheuristic algorithms has been demonstrated for many benchmark problems and in various application areas. A comprehensive review for the EHO-based algorithms and their applications are presented in this paper. Various aspects of the EHO variants for continuous optimization, combinatorial optimization, constrained optimization, and multi-objective optimization are reviewed. Future directions for research in the area of EHO are further discussed.

Keywords:  
elephant herding optimization
engineering optimization
metaheuristic
constrained optimization
multi-objective optimization

Author(s) Name:  Juan Li, Hong Lei, Amir H. Alavi, and Gai-Ge Wang

Publisher name:  MDPI

DOI:  10.3390/math8091415

Volume Information:  Volume 8

Paper Link:   https://www.mdpi.com/2227-7390/8/9/1415