Finite Convergence of Circumcentered-Reflection Method on Closed Polyhedral Cones in Euclidean Spaces

Fuente: arXiv
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Autor principal: Liao, Hongzhi
Formato: Preprint
Publicado: 2024
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author Liao, Hongzhi
author_facet Liao, Hongzhi
contents The Circumcentered Reflection Method (CRM) is a recently developed projection method for solving convex feasibility problems. It offers preferable convergence properties compared to classic methods such as the Douglas-Rachford and the alternating projections method. In this study, our first main theorem establishes that CRM can identify a feasible point in the intersection of two closed convex cones in \(\mathbb{R}^2\) from any starting point in the Euclidean plane. We then apply this theorem to intersections of two polyhedral sets in \(\mathbb{R}^2\) and two wedge-like sets in \(\mathbb{R}^n\), proving that CRM converges to a point in the intersection from any initial position finitely. Additionally, we introduce a modified technique based on CRM, called the Sphere-Centered Reflection Method. With the help of this technique, we demonstrate that CRM can locate a feasible point in finitely many iterations in the intersection of two proper polyhedral cones in \(\mathbb{R}^3\) when the initial point lies in a subset of the complement of the intersection's polar cone. Lastly, we provide an example illustrating that finite convergence may fail for the intersection of two proper polyhedral cones in \(\mathbb{R}^3\) if the initial guess is outside the designated set.
format Preprint
id arxiv_https___arxiv_org_abs_2412_00512
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Finite Convergence of Circumcentered-Reflection Method on Closed Polyhedral Cones in Euclidean Spaces
Liao, Hongzhi
Optimization and Control
The Circumcentered Reflection Method (CRM) is a recently developed projection method for solving convex feasibility problems. It offers preferable convergence properties compared to classic methods such as the Douglas-Rachford and the alternating projections method. In this study, our first main theorem establishes that CRM can identify a feasible point in the intersection of two closed convex cones in \(\mathbb{R}^2\) from any starting point in the Euclidean plane. We then apply this theorem to intersections of two polyhedral sets in \(\mathbb{R}^2\) and two wedge-like sets in \(\mathbb{R}^n\), proving that CRM converges to a point in the intersection from any initial position finitely. Additionally, we introduce a modified technique based on CRM, called the Sphere-Centered Reflection Method. With the help of this technique, we demonstrate that CRM can locate a feasible point in finitely many iterations in the intersection of two proper polyhedral cones in \(\mathbb{R}^3\) when the initial point lies in a subset of the complement of the intersection's polar cone. Lastly, we provide an example illustrating that finite convergence may fail for the intersection of two proper polyhedral cones in \(\mathbb{R}^3\) if the initial guess is outside the designated set.
title Finite Convergence of Circumcentered-Reflection Method on Closed Polyhedral Cones in Euclidean Spaces
topic Optimization and Control
url https://arxiv.org/abs/2412.00512