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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2604.00180 |
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| _version_ | 1866915904192774144 |
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| author | Zhong, Suhan Zhou, Jinling Nie, Jiawang Tang, Xindong |
| author_facet | Zhong, Suhan Zhou, Jinling Nie, Jiawang Tang, Xindong |
| contents | This paper studies the copositive optimization problem whose objective is a sparse polynomial, with linear constraints over the nonnegative orthant. We propose sparse Moment-SOS relaxations to solve it. Necessary and sufficient conditions are shown for these relaxations to be tight. In particular, we prove they are tight under the cop-SOS convexity assumption. Compared to the traditional dense ones, the sparse Moment-SOS relaxations are more computationally efficient. Numerical experiments are given to show the efficiency. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_00180 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Sparse Copositive Polynomial Optimization Zhong, Suhan Zhou, Jinling Nie, Jiawang Tang, Xindong Optimization and Control This paper studies the copositive optimization problem whose objective is a sparse polynomial, with linear constraints over the nonnegative orthant. We propose sparse Moment-SOS relaxations to solve it. Necessary and sufficient conditions are shown for these relaxations to be tight. In particular, we prove they are tight under the cop-SOS convexity assumption. Compared to the traditional dense ones, the sparse Moment-SOS relaxations are more computationally efficient. Numerical experiments are given to show the efficiency. |
| title | Sparse Copositive Polynomial Optimization |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2604.00180 |