*Article* **Elephant Herding Optimization: Variants, Hybrids, and Applications**

#### **Juan Li 1,2,3, Hong Lei 2, Amir H. Alavi 4,5,6 and Gai-Ge Wang 7,8,9,\***


Received: 8 July 2020; Accepted: 20 August 2020; Published: 24 August 2020

**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
