Multiple strategy enhanced hybrid algorithm BAGWO combining beetle antennae search and grey wolf optimizer for global optimization
Abstract This study proposes BAGWO, a novel hybrid optimization algorithm that integrates the Beetle Antennae Search algorithm (BAS) and the Grey Wolf Optimizer (GWO) to leverage their complementary strengths while enhancing their original strategies. BAGWO introduces three key improvements: the cha...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-05-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-98816-0 |
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| _version_ | 1850042651986886656 |
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| author | Fan Zhang Chuankai Liu Peng Liu Shuiting Ding Tian Qiu Jiajun Wang Huipeng Du |
| author_facet | Fan Zhang Chuankai Liu Peng Liu Shuiting Ding Tian Qiu Jiajun Wang Huipeng Du |
| author_sort | Fan Zhang |
| collection | DOAJ |
| description | Abstract This study proposes BAGWO, a novel hybrid optimization algorithm that integrates the Beetle Antennae Search algorithm (BAS) and the Grey Wolf Optimizer (GWO) to leverage their complementary strengths while enhancing their original strategies. BAGWO introduces three key improvements: the charisma concept and its update strategy based on the sigmoid function, the local exploitation frequency update strategy driven by the cosine function, and the switching strategy for the antennae length decay rate. These improvements are rigorously validated through ablation experiments. Comprehensive evaluations on 24 benchmark functions from CEC 2005 and CEC 2017, along with eight real-world engineering problems, demonstrate that BAGWO achieves stable convergence and superior optimization performance. Extensive testing and quantitative statistical analyses confirm that BAGWO significantly outperforms competing algorithms in terms of solution accuracy and stability, highlighting its strong competitiveness and potential for practical applications in global optimization. |
| format | Article |
| id | doaj-art-051dc4f05ff54d55abe8df958c4a91e0 |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-051dc4f05ff54d55abe8df958c4a91e02025-08-20T02:55:29ZengNature PortfolioScientific Reports2045-23222025-05-0115114610.1038/s41598-025-98816-0Multiple strategy enhanced hybrid algorithm BAGWO combining beetle antennae search and grey wolf optimizer for global optimizationFan Zhang0Chuankai Liu1Peng Liu2Shuiting Ding3Tian Qiu4Jiajun Wang5Huipeng Du6Research Institute of Aero-Engine, Beihang UniversityResearch Institute of Aero-Engine, Beihang UniversityResearch Institute of Aero-Engine, Beihang UniversityResearch Institute of Aero-Engine, Beihang UniversityResearch Institute of Aero-Engine, Beihang UniversityResearch Institute of Aero-Engine, Beihang UniversityResearch Institute of Aero-Engine, Beihang UniversityAbstract This study proposes BAGWO, a novel hybrid optimization algorithm that integrates the Beetle Antennae Search algorithm (BAS) and the Grey Wolf Optimizer (GWO) to leverage their complementary strengths while enhancing their original strategies. BAGWO introduces three key improvements: the charisma concept and its update strategy based on the sigmoid function, the local exploitation frequency update strategy driven by the cosine function, and the switching strategy for the antennae length decay rate. These improvements are rigorously validated through ablation experiments. Comprehensive evaluations on 24 benchmark functions from CEC 2005 and CEC 2017, along with eight real-world engineering problems, demonstrate that BAGWO achieves stable convergence and superior optimization performance. Extensive testing and quantitative statistical analyses confirm that BAGWO significantly outperforms competing algorithms in terms of solution accuracy and stability, highlighting its strong competitiveness and potential for practical applications in global optimization.https://doi.org/10.1038/s41598-025-98816-0Hybrid algorithmGrey Wolf OptimizerBeetle Antennae Search algorithmAblation experimentsGlobal optimizationBAGWO |
| spellingShingle | Fan Zhang Chuankai Liu Peng Liu Shuiting Ding Tian Qiu Jiajun Wang Huipeng Du Multiple strategy enhanced hybrid algorithm BAGWO combining beetle antennae search and grey wolf optimizer for global optimization Scientific Reports Hybrid algorithm Grey Wolf Optimizer Beetle Antennae Search algorithm Ablation experiments Global optimization BAGWO |
| title | Multiple strategy enhanced hybrid algorithm BAGWO combining beetle antennae search and grey wolf optimizer for global optimization |
| title_full | Multiple strategy enhanced hybrid algorithm BAGWO combining beetle antennae search and grey wolf optimizer for global optimization |
| title_fullStr | Multiple strategy enhanced hybrid algorithm BAGWO combining beetle antennae search and grey wolf optimizer for global optimization |
| title_full_unstemmed | Multiple strategy enhanced hybrid algorithm BAGWO combining beetle antennae search and grey wolf optimizer for global optimization |
| title_short | Multiple strategy enhanced hybrid algorithm BAGWO combining beetle antennae search and grey wolf optimizer for global optimization |
| title_sort | multiple strategy enhanced hybrid algorithm bagwo combining beetle antennae search and grey wolf optimizer for global optimization |
| topic | Hybrid algorithm Grey Wolf Optimizer Beetle Antennae Search algorithm Ablation experiments Global optimization BAGWO |
| url | https://doi.org/10.1038/s41598-025-98816-0 |
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