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| Auteurs principaux: | , , |
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| Format: | Preprint |
| Publié: |
2024
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| Sujets: | |
| Accès en ligne: | https://arxiv.org/abs/2412.13576 |
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| _version_ | 1866910043011547136 |
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| author | Liu, Wenbo Wang, Akang Yang, Wenguo |
| author_facet | Liu, Wenbo Wang, Akang Yang, Wenguo |
| contents | The augmentation scheme provides a nontraditional approach to nonlinear integer programming by iteratively refining incumbent solutions along objective-improving directions from the Graver basis. Its main computational bottleneck, however, lies in the practical difficulty of accessing such directions. To address this challenge, we develop a massively parallel heuristic for approximating Graver basis, extracting promising directions by optimizing nonconvex continuous problems using parallelizable first-order methods. Experiments on QPLIB and MINLPLib instances show that our method achieves comparable performance to advanced solvers. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_13576 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Parallel Graver Basis Extraction for Nonlinear Integer Optimization Liu, Wenbo Wang, Akang Yang, Wenguo Optimization and Control The augmentation scheme provides a nontraditional approach to nonlinear integer programming by iteratively refining incumbent solutions along objective-improving directions from the Graver basis. Its main computational bottleneck, however, lies in the practical difficulty of accessing such directions. To address this challenge, we develop a massively parallel heuristic for approximating Graver basis, extracting promising directions by optimizing nonconvex continuous problems using parallelizable first-order methods. Experiments on QPLIB and MINLPLib instances show that our method achieves comparable performance to advanced solvers. |
| title | Parallel Graver Basis Extraction for Nonlinear Integer Optimization |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2412.13576 |