Solving convex QPs with structured sparsity under indicator conditions
Fuente:
arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866910703467626496 |
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| author | Bienstock, Daniel Chen, Tongtong |
| author_facet | Bienstock, Daniel Chen, Tongtong |
| contents | We study convex optimization problems where disjoint blocks of variables are controlled by binary indicator variables that are also subject to conditions, e.g., cardinality. Several classes of important examples can be formulated in such a way that both the objective and the constraints are separable convex quadratics. We describe a family of polynomial-time approximation algorithms and negative complexity results. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_11722 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Solving convex QPs with structured sparsity under indicator conditions Bienstock, Daniel Chen, Tongtong Optimization and Control Computational Complexity Data Structures and Algorithms We study convex optimization problems where disjoint blocks of variables are controlled by binary indicator variables that are also subject to conditions, e.g., cardinality. Several classes of important examples can be formulated in such a way that both the objective and the constraints are separable convex quadratics. We describe a family of polynomial-time approximation algorithms and negative complexity results. |
| title | Solving convex QPs with structured sparsity under indicator conditions |
| topic | Optimization and Control Computational Complexity Data Structures and Algorithms |
| url | https://arxiv.org/abs/2411.11722 |