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Hauptverfasser: Alcantara, Jan Harold, Takeda, Akiko
Format: Preprint
Veröffentlicht: 2025
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Online-Zugang:https://arxiv.org/abs/2501.02752
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author Alcantara, Jan Harold
Takeda, Akiko
author_facet Alcantara, Jan Harold
Takeda, Akiko
contents The Douglas--Rachford algorithm is a classic splitting method for finding a zero of the sum of two maximal monotone operators. It has also been applied to settings that involve one weakly and one strongly monotone operator. In this work, we extend the Douglas--Rachford algorithm to address multioperator inclusion problems involving $m$ ($m\geq 2$) weakly and strongly monotone operators, reformulated as a two-operator inclusion in a product space. By selecting appropriate parameters, we establish the convergence of the algorithm to a fixed point, from which solutions can be extracted. Furthermore, we illustrate its applicability to sum-of-$m$-functions minimization problems characterized by weakly convex and strongly convex functions. For general nonconvex problems in finite-dimensional spaces, comprising Lipschitz continuously differentiable functions and a proper closed function, we provide global subsequential convergence guarantees.
format Preprint
id arxiv_https___arxiv_org_abs_2501_02752
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Douglas--Rachford algorithm for nonmonotone multioperator inclusion problems
Alcantara, Jan Harold
Takeda, Akiko
Optimization and Control
47H10, 49M27
The Douglas--Rachford algorithm is a classic splitting method for finding a zero of the sum of two maximal monotone operators. It has also been applied to settings that involve one weakly and one strongly monotone operator. In this work, we extend the Douglas--Rachford algorithm to address multioperator inclusion problems involving $m$ ($m\geq 2$) weakly and strongly monotone operators, reformulated as a two-operator inclusion in a product space. By selecting appropriate parameters, we establish the convergence of the algorithm to a fixed point, from which solutions can be extracted. Furthermore, we illustrate its applicability to sum-of-$m$-functions minimization problems characterized by weakly convex and strongly convex functions. For general nonconvex problems in finite-dimensional spaces, comprising Lipschitz continuously differentiable functions and a proper closed function, we provide global subsequential convergence guarantees.
title Douglas--Rachford algorithm for nonmonotone multioperator inclusion problems
topic Optimization and Control
47H10, 49M27
url https://arxiv.org/abs/2501.02752