Douglas--Rachford for multioperator comonotone inclusions with applications to multiblock optimization

Fuente: arXiv
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Autori principali: Alcantara, Jan Harold, Dao, Minh N., Takeda, Akiko
Natura: Preprint
Pubblicazione: 2025
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author Alcantara, Jan Harold
Dao, Minh N.
Takeda, Akiko
author_facet Alcantara, Jan Harold
Dao, Minh N.
Takeda, Akiko
contents We study the convergence of the adaptive Douglas--Rachford (aDR) algorithm for solving a multioperator inclusion problem involving the sum of maximally comonotone operators. To address such problems, we adopt a product space reformulation that accommodates nonconvex-valued operators, which is essential when dealing with comonotone mappings. We establish convergence of the aDR method under comonotonicity assumptions, subject to suitable conditions on the algorithm parameters and comonotonicity moduli of the operators. Our analysis leverages the Attouch--Théra duality framework, which allows us to study the convergence of the aDR algorithm via its application to the dual inclusion problem. As an application, we derive a multiblock ADMM-type algorithm for structured convex and nonconvex optimization problems by applying the aDR algorithm to the operator inclusion formulation of the KKT system. The resulting method extends to multiblock and nonconvex settings the classical duality between the Douglas--Rachford algorithm and the alternating direction method of multipliers in the convex two-block case. Moreover, we establish convergence guarantees for both the fully convex and strongly convex-weakly convex regimes.
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id arxiv_https___arxiv_org_abs_2506_22928
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publishDate 2025
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spellingShingle Douglas--Rachford for multioperator comonotone inclusions with applications to multiblock optimization
Alcantara, Jan Harold
Dao, Minh N.
Takeda, Akiko
Optimization and Control
We study the convergence of the adaptive Douglas--Rachford (aDR) algorithm for solving a multioperator inclusion problem involving the sum of maximally comonotone operators. To address such problems, we adopt a product space reformulation that accommodates nonconvex-valued operators, which is essential when dealing with comonotone mappings. We establish convergence of the aDR method under comonotonicity assumptions, subject to suitable conditions on the algorithm parameters and comonotonicity moduli of the operators. Our analysis leverages the Attouch--Théra duality framework, which allows us to study the convergence of the aDR algorithm via its application to the dual inclusion problem. As an application, we derive a multiblock ADMM-type algorithm for structured convex and nonconvex optimization problems by applying the aDR algorithm to the operator inclusion formulation of the KKT system. The resulting method extends to multiblock and nonconvex settings the classical duality between the Douglas--Rachford algorithm and the alternating direction method of multipliers in the convex two-block case. Moreover, we establish convergence guarantees for both the fully convex and strongly convex-weakly convex regimes.
title Douglas--Rachford for multioperator comonotone inclusions with applications to multiblock optimization
topic Optimization and Control
url https://arxiv.org/abs/2506.22928