A greedy non‐hierarchical grey wolf optimizer for real‐world optimization
Abstract Grey wolf optimization (GWO) algorithm is a new emerging algorithm that is based on the social hierarchy of grey wolves as well as their hunting and cooperation strategies. Introduced in 2014, this algorithm has been used by a large number of researchers and designers, such that the number...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Wiley
2021-06-01
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| Series: | Electronics Letters |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/ell2.12176 |
| _version_ | 1797900604977184768 |
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| author | Ebrahim Akbari Abolfazl Rahimnejad Stephen Andrew Gadsden |
| author_facet | Ebrahim Akbari Abolfazl Rahimnejad Stephen Andrew Gadsden |
| author_sort | Ebrahim Akbari |
| collection | DOAJ |
| description | Abstract Grey wolf optimization (GWO) algorithm is a new emerging algorithm that is based on the social hierarchy of grey wolves as well as their hunting and cooperation strategies. Introduced in 2014, this algorithm has been used by a large number of researchers and designers, such that the number of citations to the original paper exceeded many other algorithms. In a recent study by Niu et al., one of the main drawbacks of this algorithm for optimizing real‐world problems was introduced. In summary, they showed that GWO's performance degrades as the optimal solution of the problem diverges from 0. In this paper, by introducing a straightforward modification to the original GWO algorithm, that is, neglecting its social hierarchy, the authors were able to largely eliminate this defect and open a new perspective for future use of this algorithm. The efficiency of the proposed method was validated by applying it to benchmark and real‐world engineering problems. |
| first_indexed | 2024-04-10T08:48:37Z |
| format | Article |
| id | doaj.art-feadca1c120544c887d2811bc126812a |
| institution | Directory Open Access Journal |
| issn | 0013-5194 1350-911X |
| language | English |
| last_indexed | 2024-04-10T08:48:37Z |
| publishDate | 2021-06-01 |
| publisher | Wiley |
| record_format | Article |
| series | Electronics Letters |
| spelling | doaj.art-feadca1c120544c887d2811bc126812a2023-02-22T06:36:15ZengWileyElectronics Letters0013-51941350-911X2021-06-01571349950110.1049/ell2.12176A greedy non‐hierarchical grey wolf optimizer for real‐world optimizationEbrahim Akbari0Abolfazl Rahimnejad1Stephen Andrew Gadsden2Department of Electrical Engineering University of Isfahan Isfahan IranCollege of Engineering and Physical Sciences University of Guelph Guelph N1G 2W1 CanadaCollege of Engineering and Physical Sciences University of Guelph Guelph N1G 2W1 CanadaAbstract Grey wolf optimization (GWO) algorithm is a new emerging algorithm that is based on the social hierarchy of grey wolves as well as their hunting and cooperation strategies. Introduced in 2014, this algorithm has been used by a large number of researchers and designers, such that the number of citations to the original paper exceeded many other algorithms. In a recent study by Niu et al., one of the main drawbacks of this algorithm for optimizing real‐world problems was introduced. In summary, they showed that GWO's performance degrades as the optimal solution of the problem diverges from 0. In this paper, by introducing a straightforward modification to the original GWO algorithm, that is, neglecting its social hierarchy, the authors were able to largely eliminate this defect and open a new perspective for future use of this algorithm. The efficiency of the proposed method was validated by applying it to benchmark and real‐world engineering problems.https://doi.org/10.1049/ell2.12176Optimisation techniquesOptimisationOptimisation techniques |
| spellingShingle | Ebrahim Akbari Abolfazl Rahimnejad Stephen Andrew Gadsden A greedy non‐hierarchical grey wolf optimizer for real‐world optimization Electronics Letters Optimisation techniques Optimisation Optimisation techniques |
| title | A greedy non‐hierarchical grey wolf optimizer for real‐world optimization |
| title_full | A greedy non‐hierarchical grey wolf optimizer for real‐world optimization |
| title_fullStr | A greedy non‐hierarchical grey wolf optimizer for real‐world optimization |
| title_full_unstemmed | A greedy non‐hierarchical grey wolf optimizer for real‐world optimization |
| title_short | A greedy non‐hierarchical grey wolf optimizer for real‐world optimization |
| title_sort | greedy non hierarchical grey wolf optimizer for real world optimization |
| topic | Optimisation techniques Optimisation Optimisation techniques |
| url | https://doi.org/10.1049/ell2.12176 |
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