Orthogonal Learning Rosenbrock’s Direct Rotation with the Gazelle Optimization Algorithm for Global Optimization
An efficient optimization method is needed to address complicated problems and find optimal solutions. The gazelle optimization algorithm (GOA) is a global stochastic optimizer that is straightforward to comprehend and has powerful search capabilities. Nevertheless, the GOA is unsuitable for address...
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| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , |
| منشور في: |
2022
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://depot.sorbonne.ae/handle/20.500.12458/1335 |
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| _version_ | 1857415062364356608 |
|---|---|
| author | Abu Zitar, Raed |
| author2 | Abualigah, Laith Diabat, Ali |
| author2_role | author author |
| author_facet | Abu Zitar, Raed Abualigah, Laith Diabat, Ali |
| author_role | author |
| dc.creator.none.fl_str_mv | Abu Zitar, Raed Abualigah, Laith Diabat, Ali |
| dc.date.none.fl_str_mv | 2022-12-05T05:02:34Z 2022-12-05T05:02:34Z 2022 |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | 10.3390/math10234509 2227-7390 https://depot.sorbonne.ae/handle/20.500.12458/1335 10.3390/math10234509 |
| dc.language.none.fl_str_mv | en |
| dc.relation.none.fl_str_mv | Mathematics |
| dc.subject.none.fl_str_mv | orthogonal learning (OL) Rosenbrock’s direct rotational (RDR) gazelle optimization algorithm (GOA) CEC2017 data clustering optimization problems |
| dc.title.none.fl_str_mv | Orthogonal Learning Rosenbrock’s Direct Rotation with the Gazelle Optimization Algorithm for Global Optimization |
| dc.type.none.fl_str_mv | Controlled Vocabulary for Resource Type Genres::text::periodical::journal::contribution to journal::journal article |
| description | An efficient optimization method is needed to address complicated problems and find optimal solutions. The gazelle optimization algorithm (GOA) is a global stochastic optimizer that is straightforward to comprehend and has powerful search capabilities. Nevertheless, the GOA is unsuitable for addressing multimodal, hybrid functions, and data mining problems. Therefore, the current paper proposes the orthogonal learning (OL) method with Rosenbrock’s direct rotation strategy to improve the GOA and sustain the solution variety (IGOA). We performed comprehensive experiments based on various functions, including 23 classical and IEEE CEC2017 problems. Moreover, eight data clustering problems taken from the UCI repository were tested to verify the proposed method’s performance further. The IGOA was compared with several other proposed meta-heuristic algorithms. Moreover, the Wilcoxon signed-rank test further assessed the experimental results to conduct more systematic data analyses. The IGOA surpassed other comparative optimizers in terms of convergence speed and precision. The empirical results show that the proposed IGOA achieved better outcomes than the basic GOA and other state-of-the-art methods and performed better in terms of solution quality. |
| id | sorbonner_4738500f72dc25dae2e938e5bfb24493 |
| identifier_str_mv | 10.3390/math10234509 2227-7390 |
| language_invalid_str_mv | en |
| network_acronym_str | sorbonner |
| network_name_str | Sorbonne University Abu Dhabi repository |
| oai_identifier_str | oai:depot.sorbonne.ae:20.500.12458/1335 |
| publishDate | 2022 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Orthogonal Learning Rosenbrock’s Direct Rotation with the Gazelle Optimization Algorithm for Global OptimizationAbu Zitar, RaedAbualigah, LaithDiabat, Aliorthogonal learning (OL)Rosenbrock’s direct rotational (RDR)gazelle optimization algorithm (GOA)CEC2017data clusteringoptimization problemsAn efficient optimization method is needed to address complicated problems and find optimal solutions. The gazelle optimization algorithm (GOA) is a global stochastic optimizer that is straightforward to comprehend and has powerful search capabilities. Nevertheless, the GOA is unsuitable for addressing multimodal, hybrid functions, and data mining problems. Therefore, the current paper proposes the orthogonal learning (OL) method with Rosenbrock’s direct rotation strategy to improve the GOA and sustain the solution variety (IGOA). We performed comprehensive experiments based on various functions, including 23 classical and IEEE CEC2017 problems. Moreover, eight data clustering problems taken from the UCI repository were tested to verify the proposed method’s performance further. The IGOA was compared with several other proposed meta-heuristic algorithms. Moreover, the Wilcoxon signed-rank test further assessed the experimental results to conduct more systematic data analyses. The IGOA surpassed other comparative optimizers in terms of convergence speed and precision. The empirical results show that the proposed IGOA achieved better outcomes than the basic GOA and other state-of-the-art methods and performed better in terms of solution quality.2022-12-05T05:02:34Z2022-12-05T05:02:34Z2022Controlled Vocabulary for Resource Type Genres::text::periodical::journal::contribution to journal::journal articleapplication/pdf10.3390/math102345092227-7390https://depot.sorbonne.ae/handle/20.500.12458/133510.3390/math10234509enMathematicsoai:depot.sorbonne.ae:20.500.12458/13352024-09-11T10:56:46Z |
| spellingShingle | Orthogonal Learning Rosenbrock’s Direct Rotation with the Gazelle Optimization Algorithm for Global Optimization Abu Zitar, Raed orthogonal learning (OL) Rosenbrock’s direct rotational (RDR) gazelle optimization algorithm (GOA) CEC2017 data clustering optimization problems |
| title | Orthogonal Learning Rosenbrock’s Direct Rotation with the Gazelle Optimization Algorithm for Global Optimization |
| title_full | Orthogonal Learning Rosenbrock’s Direct Rotation with the Gazelle Optimization Algorithm for Global Optimization |
| title_fullStr | Orthogonal Learning Rosenbrock’s Direct Rotation with the Gazelle Optimization Algorithm for Global Optimization |
| title_full_unstemmed | Orthogonal Learning Rosenbrock’s Direct Rotation with the Gazelle Optimization Algorithm for Global Optimization |
| title_short | Orthogonal Learning Rosenbrock’s Direct Rotation with the Gazelle Optimization Algorithm for Global Optimization |
| title_sort | Orthogonal Learning Rosenbrock’s Direct Rotation with the Gazelle Optimization Algorithm for Global Optimization |
| topic | orthogonal learning (OL) Rosenbrock’s direct rotational (RDR) gazelle optimization algorithm (GOA) CEC2017 data clustering optimization problems |
| url | https://depot.sorbonne.ae/handle/20.500.12458/1335 |