A quasi-opposition learning and chaos local search based on walrus optimization for global optimization problems
Abstract The Walrus Optimization (WO) algorithm, as an emerging metaheuristic algorithm, has shown excellent performance in problem-solving, however it still faces issues such as slow convergence and susceptibility to getting trapped in local optima. To this end, the study proposes a novel WO enhanc...
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| Главные авторы: | , , , , |
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| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
Nature Portfolio
2025-01-01
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| Серии: | Scientific Reports |
| Предметы: | |
| Online-ссылка: | https://doi.org/10.1038/s41598-025-85751-3 |
| Метки: |
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