Splitting algorithms for solving state-dependent maximal monotone inclusion problems

We consider the state-dependent maximal monotone inclusion problem and propose forward-backward splitting algorithms for solving it. Strong convergence of the proposed algorithms is established under suitable conditions. For the special separable case, we present an improved Douglas-Rachford variant...

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Bibliographic Details
Published in:	Optimization Vol. 74; no. 9; pp. 2113 - 2136
Main Authors:	Li, Xiaoxiao, Dong, Qiao-Li, Gibali, Aviv
Format:	Journal Article
Language:	English
Published:	Taylor & Francis 04.07.2025
Subjects:	Douglas-Rachford splitting algorithm forward-backward splitting algorithm inertial acceleration algorithm State-dependent maximal monotone inclusion
ISSN:	0233-1934, 1029-4945
Online Access:	Get full text
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Summary:	We consider the state-dependent maximal monotone inclusion problem and propose forward-backward splitting algorithms for solving it. Strong convergence of the proposed algorithms is established under suitable conditions. For the special separable case, we present an improved Douglas-Rachford variant that can be easily implemented. Moreover, some accelerated forward-backward splitting algorithms are also presented. Preliminary numerical experiments with comparisons to existing results are presented, illustrating the advantages of our methods.
ISSN:	0233-1934 1029-4945
DOI:	10.1080/02331934.2024.2341942