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Harris Hawk Optimization: A Survey onVariants and Applications
In this review, we intend to present a complete literature survey on the conception and variants of the recent successful optimization algorithm, Harris Hawk optimizer (HHO), along with an updated set of applications in well-established works. For this purpose, we first present an overview of HHO, i...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9252670/ https://www.ncbi.nlm.nih.gov/pubmed/35795744 http://dx.doi.org/10.1155/2022/2218594 |
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author | Tripathy, B. K. Reddy Maddikunta, Praveen Kumar Pham, Quoc-Viet Gadekallu, Thippa Reddy Dev, Kapal Pandya, Sharnil ElHalawany, Basem M. |
author_facet | Tripathy, B. K. Reddy Maddikunta, Praveen Kumar Pham, Quoc-Viet Gadekallu, Thippa Reddy Dev, Kapal Pandya, Sharnil ElHalawany, Basem M. |
author_sort | Tripathy, B. K. |
collection | PubMed |
description | In this review, we intend to present a complete literature survey on the conception and variants of the recent successful optimization algorithm, Harris Hawk optimizer (HHO), along with an updated set of applications in well-established works. For this purpose, we first present an overview of HHO, including its logic of equations and mathematical model. Next, we focus on reviewing different variants of HHO from the available well-established literature. To provide readers a deep vision and foster the application of the HHO, we review the state-of-the-art improvements of HHO, focusing mainly on fuzzy HHO and a new intuitionistic fuzzy HHO algorithm. We also review the applications of HHO in enhancing machine learning operations and in tackling engineering optimization problems. This survey can cover different aspects of HHO and its future applications to provide a basis for future research in the development of swarm intelligence paths and the use of HHO for real-world problems. |
format | Online Article Text |
id | pubmed-9252670 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-92526702022-07-05 Harris Hawk Optimization: A Survey onVariants and Applications Tripathy, B. K. Reddy Maddikunta, Praveen Kumar Pham, Quoc-Viet Gadekallu, Thippa Reddy Dev, Kapal Pandya, Sharnil ElHalawany, Basem M. Comput Intell Neurosci Review Article In this review, we intend to present a complete literature survey on the conception and variants of the recent successful optimization algorithm, Harris Hawk optimizer (HHO), along with an updated set of applications in well-established works. For this purpose, we first present an overview of HHO, including its logic of equations and mathematical model. Next, we focus on reviewing different variants of HHO from the available well-established literature. To provide readers a deep vision and foster the application of the HHO, we review the state-of-the-art improvements of HHO, focusing mainly on fuzzy HHO and a new intuitionistic fuzzy HHO algorithm. We also review the applications of HHO in enhancing machine learning operations and in tackling engineering optimization problems. This survey can cover different aspects of HHO and its future applications to provide a basis for future research in the development of swarm intelligence paths and the use of HHO for real-world problems. Hindawi 2022-06-27 /pmc/articles/PMC9252670/ /pubmed/35795744 http://dx.doi.org/10.1155/2022/2218594 Text en Copyright © 2022 B. K. Tripathy et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Article Tripathy, B. K. Reddy Maddikunta, Praveen Kumar Pham, Quoc-Viet Gadekallu, Thippa Reddy Dev, Kapal Pandya, Sharnil ElHalawany, Basem M. Harris Hawk Optimization: A Survey onVariants and Applications |
title | Harris Hawk Optimization: A Survey onVariants and Applications |
title_full | Harris Hawk Optimization: A Survey onVariants and Applications |
title_fullStr | Harris Hawk Optimization: A Survey onVariants and Applications |
title_full_unstemmed | Harris Hawk Optimization: A Survey onVariants and Applications |
title_short | Harris Hawk Optimization: A Survey onVariants and Applications |
title_sort | harris hawk optimization: a survey onvariants and applications |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9252670/ https://www.ncbi.nlm.nih.gov/pubmed/35795744 http://dx.doi.org/10.1155/2022/2218594 |
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