- Title
- On Slater’s condition and finite convergence of the Douglas–Rachford algorithm for solving convex feasibility problems in Euclidean spaces
- Creator
- Bauschke, Heinz; Dao, Minh; Noll, Dominikus; Phan, Hung
- Date
- 2016
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/185575
- Identifier
- vital:16693
- Identifier
-
https://doi.org/10.1007/s10898-015-0373-5
- Identifier
- ISBN:0925-5001
- Abstract
- The Douglas–Rachford algorithm is a classical and very successful method for solving optimization and feasibility problems. In this paper, we provide novel conditions sufficient for finite convergence in the context of convex feasibility problems. Our analysis builds upon, and considerably extends, pioneering work by Spingarn. Specifically, we obtain finite convergence in the presence of Slater’s condition in the affine-polyhedral and in a hyperplanar-epigraphical case. Various examples illustrate our results. Numerical experiments demonstrate the competitiveness of the Douglas–Rachford algorithm for solving linear equations with a positivity constraint when compared to the method of alternating projections and the method of reflection–projection.
- Publisher
- New York: Springer US
- Relation
- Journal of global optimization Vol. 65, no. 2 (2016), p. 329-349
- Rights
- All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
- Rights
- Copyright Springer
- Subject
- Algorithms; Analysis; Computer Science; Construction; Convergence; Euclidean space; Experiments; Feasibility; Linear equations; Mathematical analysis; Mathematical models; Mathematics; Mathematics and Statistics; Operations Research/Decision Theory; Optimization; Optimization and Control; Projection; Real Functions; Studies; 4602 Artificial intelligence; 4901 Applied mathematics; 4903 Numerical and computational mathematics
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