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Article

Elephant Herding Optimization: Variants, Hybrids, and Applications

by 1,2,3, 2, 4,5,6 and 7,8,9,*
1
School of Artificial Intelligence, Wuhan Technology and Business University, Wuhan 430065, China
2
School of Artificial Intelligence, Wuchang University of Technology, Wuhan 430223, China
3
Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun 130012, China
4
Department of Civil and Environmental Engineering, University of Pittsburgh, Pittsburgh, PA 15261, USA
5
Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15261, USA
6
Department of Computer Science and Information Engineering, Asia University, Taichung 41354, Taiwan
7
Department of Computer Science and Technology, Ocean University of China, Qingdao 266100, China
8
Institute of Algorithm and Big Data Analysis, Northeast Normal University, Changchun 130117, China
9
School of Computer Science and Information Technology, Northeast Normal University, Changchun 130117, China
*
Author to whom correspondence should be addressed.
Mathematics 2020, 8(9), 1415; https://doi.org/10.3390/math8091415
Received: 8 July 2020 / Revised: 14 August 2020 / Accepted: 20 August 2020 / Published: 24 August 2020
(This article belongs to the Special Issue Evolutionary Computation 2020)
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. View Full-Text
Keywords: elephant herding optimization; engineering optimization; metaheuristic; constrained optimization; multi-objective optimization elephant herding optimization; engineering optimization; metaheuristic; constrained optimization; multi-objective optimization
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MDPI and ACS Style

Li, J.; Lei, H.; Alavi, A.H.; Wang, G.-G. Elephant Herding Optimization: Variants, Hybrids, and Applications. Mathematics 2020, 8, 1415. https://doi.org/10.3390/math8091415

AMA Style

Li J, Lei H, Alavi AH, Wang G-G. Elephant Herding Optimization: Variants, Hybrids, and Applications. Mathematics. 2020; 8(9):1415. https://doi.org/10.3390/math8091415

Chicago/Turabian Style

Li, Juan, Hong Lei, Amir H. Alavi, and Gai-Ge Wang. 2020. "Elephant Herding Optimization: Variants, Hybrids, and Applications" Mathematics 8, no. 9: 1415. https://doi.org/10.3390/math8091415

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