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Main Authors: Shen, Yuting, Liang, Jingwei
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2504.11313
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author Shen, Yuting
Liang, Jingwei
author_facet Shen, Yuting
Liang, Jingwei
contents Feasibility problem aims to find a common point of two or more closed (convex) sets whose intersection is nonempty. In the literature, projection based algorithms are widely adopted to solve the problem, such as the method of alternating projection (MAP), and Douglas--Rachford splitting method (DR). The performance of the methods are governed by the geometric properties of the underlying sets. For example, the fixed-point sequence of the Douglas--Rachford splitting method exhibits a spiraling behavior when solving the feasibility problem of two subspaces, leading to a slow convergence speed and slower than MAP. However, when the problem at hand is non-polyhedral, DR can demonstrate significant faster performance. Motivated by the behaviors of the DR method, in this paper we propose a new algorithm for solving convex feasibility problems. The method is designed based on DR method by further incorporating a composition of projection and reflection. A non-stationary version of the method is also designed, aiming to achieve faster practical performance. Theoretical guarantees of the proposed schemes are provided and supported by numerical experiments.
format Preprint
id arxiv_https___arxiv_org_abs_2504_11313
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A Composed Alternating Relaxed Projection Algorithm for Feasibility Problem
Shen, Yuting
Liang, Jingwei
Optimization and Control
Feasibility problem aims to find a common point of two or more closed (convex) sets whose intersection is nonempty. In the literature, projection based algorithms are widely adopted to solve the problem, such as the method of alternating projection (MAP), and Douglas--Rachford splitting method (DR). The performance of the methods are governed by the geometric properties of the underlying sets. For example, the fixed-point sequence of the Douglas--Rachford splitting method exhibits a spiraling behavior when solving the feasibility problem of two subspaces, leading to a slow convergence speed and slower than MAP. However, when the problem at hand is non-polyhedral, DR can demonstrate significant faster performance. Motivated by the behaviors of the DR method, in this paper we propose a new algorithm for solving convex feasibility problems. The method is designed based on DR method by further incorporating a composition of projection and reflection. A non-stationary version of the method is also designed, aiming to achieve faster practical performance. Theoretical guarantees of the proposed schemes are provided and supported by numerical experiments.
title A Composed Alternating Relaxed Projection Algorithm for Feasibility Problem
topic Optimization and Control
url https://arxiv.org/abs/2504.11313