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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2409.05002 |
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| _version_ | 1866916827754397696 |
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| author | Luo, Zhenhua Yuan, Gonglin Pham, Hongtruong |
| author_facet | Luo, Zhenhua Yuan, Gonglin Pham, Hongtruong |
| contents | We integrate the diagonal quasi-Newton update approach with the enhanced BFGS formula proposed by Wei, Z., Yu, G., Yuan, G., Lian, Z. \cite{b1}, incorporating extrapolation techniques and inertia acceleration technology. This method, designed specifically for non-convex constrained problems, requires that the search direction ensures sufficient descent and establishes global linear convergence. Such a design has yielded exceptionally favorable data results. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_05002 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Diagonal BFGS Update Algorithm with Inertia Acceleration Technology for Minimizations Luo, Zhenhua Yuan, Gonglin Pham, Hongtruong Optimization and Control We integrate the diagonal quasi-Newton update approach with the enhanced BFGS formula proposed by Wei, Z., Yu, G., Yuan, G., Lian, Z. \cite{b1}, incorporating extrapolation techniques and inertia acceleration technology. This method, designed specifically for non-convex constrained problems, requires that the search direction ensures sufficient descent and establishes global linear convergence. Such a design has yielded exceptionally favorable data results. |
| title | A Diagonal BFGS Update Algorithm with Inertia Acceleration Technology for Minimizations |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2409.05002 |