A Comprehensive Survey of the Harmony Search Algorithm in Clustering Applications

The Harmony Search Algorithm (HSA) is a swarm intelligence optimization algorithm which has been successfully applied to a broad range of clustering applications, including data clustering, text clustering, fuzzy clustering, image processing, and wireless sensor networks. We provide a comprehensive...

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Published in:	Applied sciences Vol. 10; no. 11; p. 3827
Main Authors:	Abualigah, Laith, Diabat, Ali, Geem, Zong Woo
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.06.2020
Subjects:	Algorithms Analysis Clustering Clustering (Computers) clustering applications harmony search algorithm Heuristic Improvisation Mathematical optimization meta-heuristic optimization algorithms Methods Optimization algorithms optimization problems Optimization techniques Population Researchers Swarm intelligence Variables United States South Korea United Arab Emirates
ISSN:	2076-3417, 2076-3417
Online Access:	Get full text
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Abstract	The Harmony Search Algorithm (HSA) is a swarm intelligence optimization algorithm which has been successfully applied to a broad range of clustering applications, including data clustering, text clustering, fuzzy clustering, image processing, and wireless sensor networks. We provide a comprehensive survey of the literature on HSA and its variants, analyze its strengths and weaknesses, and suggest future research directions.
AbstractList	The Harmony Search Algorithm (HSA) is a swarm intelligence optimization algorithm which has been successfully applied to a broad range of clustering applications, including data clustering, text clustering, fuzzy clustering, image processing, and wireless sensor networks. We provide a comprehensive survey of the literature on HSA and its variants, analyze its strengths and weaknesses, and suggest future research directions. The Harmony Search Algorithm (HSA) is a swarm intelligence optimization algorithm which has been successfully applied to a broad range of clustering applications, including data clustering, text clustering, fuzzy clustering, image processing, and wireless sensor networks. We provide a comprehensive survey of the literature on HSA and its variants, analyze its strengths and weaknesses, and suggest future research directions. Keywords: harmony search algorithm; meta-heuristic optimization algorithms; optimization problems; clustering applications
Audience	Academic
Author	Abualigah, Laith Geem, Zong Woo Diabat, Ali
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SubjectTerms	Algorithms Analysis Clustering Clustering (Computers) clustering applications harmony search algorithm Heuristic Improvisation Mathematical optimization meta-heuristic optimization algorithms Methods Optimization algorithms optimization problems Optimization techniques Population Researchers Swarm intelligence Variables
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Title	A Comprehensive Survey of the Harmony Search Algorithm in Clustering Applications
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