Cyclic Relaxed Douglas-Rachford Splitting for Inconsistent Nonconvex Feasibility
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arXiv
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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866915980192514048 |
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| author | Dinh, Thi Lan Jansen, G. S. Matthijs Luke, D. Russell |
| author_facet | Dinh, Thi Lan Jansen, G. S. Matthijs Luke, D. Russell |
| contents | We study the cyclic relaxed Douglas-Rachford algorithm for possibly nonconvex, and inconsistent feasibility problems. This algorithm can be viewed as a convex relaxation between the cyclic Douglas-Rachford algorithm first introduced by Borwein and Tam [2014] and the classical cyclic projections algorithm. We characterize the fixed points of the cyclic relaxed Douglas-Rachford algorithm and show the relation of the {\em shadows} of these fixed points to the fixed points of the cyclic projections algorithm. Finally, we provide conditions that guarantee local quantitative convergence estimates in the nonconvex, inconsistent setting. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_12285 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Cyclic Relaxed Douglas-Rachford Splitting for Inconsistent Nonconvex Feasibility Dinh, Thi Lan Jansen, G. S. Matthijs Luke, D. Russell Optimization and Control 65K10, 49J53, 49K40, 49M05, 65K05, 90C26, 49M20 We study the cyclic relaxed Douglas-Rachford algorithm for possibly nonconvex, and inconsistent feasibility problems. This algorithm can be viewed as a convex relaxation between the cyclic Douglas-Rachford algorithm first introduced by Borwein and Tam [2014] and the classical cyclic projections algorithm. We characterize the fixed points of the cyclic relaxed Douglas-Rachford algorithm and show the relation of the {\em shadows} of these fixed points to the fixed points of the cyclic projections algorithm. Finally, we provide conditions that guarantee local quantitative convergence estimates in the nonconvex, inconsistent setting. |
| title | Cyclic Relaxed Douglas-Rachford Splitting for Inconsistent Nonconvex Feasibility |
| topic | Optimization and Control 65K10, 49J53, 49K40, 49M05, 65K05, 90C26, 49M20 |
| url | https://arxiv.org/abs/2502.12285 |