Multi-step inertial strictly contractive PRSM algorithms for convex programming problems with applications

  • Zhao Deng*
  • , Deren Han
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

The Peaceman–Rachford splitting method (PRSM) has been widely studied in recent years because of its excellent numerical performance, especially with inertial acceleration. In this paper, we propose a multi-step inertial strictly contractive PRSM (shortly, MISCPRSM) for solving convex optimization problems, which has not been studied before. This paper aims to give an exhaustive analysis of the value relationship between multiple inertial parameters. The second subproblem utilizes an additional customized indefinite proximal term in order to obtain a closed-form solution. The global convergence and complexity result of the introduced method are analyzed by using variational inequality and basic inequalities. Finally, through simulation and computed tomography experiments, the effectiveness and robustness of the MISCPRSM are proved, and the detailed values of inertial parameters are given.

Original languageEnglish
Article number115469
JournalJournal of Computational and Applied Mathematics
Volume437
DOIs
StatePublished - Feb 2024

Keywords

  • Convex programming
  • Global convergence
  • Indefinite proximal term
  • Inertial step
  • Peaceman–Rachford splitting method
  • Variational inequality

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