An Inexact Inertial Projective Splitting Algorithm with Strong Convergence

M. Marques Alves (), J. E. Navarro Caballero () and R. T. Marcavillaca ()
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M. Marques Alves: Universidade Federal de Santa Catarina
J. E. Navarro Caballero: Universidade Federal de Santa Catarina
R. T. Marcavillaca: Universidad de Chile

Journal of Optimization Theory and Applications, 2025, vol. 207, issue 3, No 25, 33 pages

Abstract: Abstract We propose and study a strongly convergent inexact inertial projective splitting (PS) algorithm for finding zeros of composite monotone inclusion problems involving the sum of finitely many maximal monotone operators. Strong convergence of the iterates is ensured by projections onto the intersection of appropriately defined half-spaces, even in the absence of inertial effects. We also establish iteration-complexity results for the proposed PS method, which likewise hold without requiring inertial terms. The algorithm includes two inertial sequences, controlled by parameters satisfying mild conditions, while preserving strong convergence and enabling iteration-complexity analysis. Furthermore, for more structured monotone inclusion problems, we derive two variants of the main algorithm that employ forward-backward and forward-backward-forward steps.

Keywords: Projective Splitting; Inertial Algorithms; Strong Convergence; Forward-Backward Methods; 47H05; 49M27; 90C33 (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10957-025-02827-w

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