NDLI: Elephant Herding Optimization

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Elephant Herding Optimization

Content Provider	Scilit
Author	Vasuki, A.
Copyright Year	2020
Description	The elephant herding optimization (EHO) algorithm is a swarm intelligence algorithm based on the herding behavior of elephants. The swarm intelligence-based algorithms are metaheuristic algorithms and provide solutions to complex real-world problems with reduced time complexity. These algorithms are modeled on the collective intelligence and social interactions among swarms of animals, birds, and insects. The solutions found by these metaheuristic algorithms might not be accurate, but they are close enough to the exact solution to be optimum. This is the main advantage of evolutionary as well as swarm-based algorithms. Since the particle swarm optimization (PSO) algorithm was first proposed in 1995, several swarm-based optimization algorithms have been invented, and the EHO is one such algorithm based on the herding behavior of elephants that was developed in 2015 [1,2]. The myriad of problems that occur in real-life applications has motivated the development of nature-inspired optimization algorithms since the traditional methods do not produce satisfactory results for all kinds of problems. Evolution in nature has motivated the invention of several optimization algorithms, and these algorithms are either based on evolutionary principles and/or swarm intelligence. Book Name: Nature-Inspired Optimization Algorithms
Related Links	https://content.taylorfrancis.com/books/download?dac=C2019-0-98738-8&isbn=9780429289071&doi=10.1201/9780429289071-16&format=pdf
Ending Page	218
Page Count	8
Starting Page	211
DOI	10.1201/9780429289071-16
Language	English
Publisher	Informa UK Limited
Publisher Date	2020-05-31
Access Restriction	Open
Subject Keyword	Book Name: Nature-Inspired Optimization Algorithms Cybernetical Science Information Systems Intelligence Optimization Algorithms Metaheuristic Algorithms Algorithm Based
Content Type	Text
Resource Type	Chapter

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