A comprehensive survey of the harmony search algorithm in clustering applications

Laith Abualigah; Ali Diabat; Zong Woo Geem

doi:10.3390/app10113827

A comprehensive survey of the harmony search algorithm in clustering applications

Laith Abualigah, Ali Diabat, Zong Woo Geem

Research output: Contribution to journal › Article › peer-review

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.

Original language	English (US)
Article number	3827
Journal	Applied Sciences (Switzerland)
Volume	10
Issue number	11
DOIs	https://doi.org/10.3390/app10113827
State	Published - Jun 1 2020

Keywords

Clustering applications
Harmony search algorithm
Meta-heuristic optimization algorithms
Optimization problems

ASJC Scopus subject areas

General Materials Science
Instrumentation
General Engineering
Process Chemistry and Technology
Computer Science Applications
Fluid Flow and Transfer Processes

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10.3390/app10113827

Cite this

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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.",

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author = "Laith Abualigah and Ali Diabat and Geem, {Zong Woo}",

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KW - Meta-heuristic optimization algorithms

KW - Optimization problems

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A comprehensive survey of the harmony search algorithm in clustering applications

Abstract

Keywords

ASJC Scopus subject areas

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