期刊论文详细信息
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS 卷:374
Inertial proximal strictly contractive Peaceman-Rachford splitting method with an indefinite term for convex optimization
Article
Deng, Zhao1  Liu, Sanyang1 
[1] Xidian Univ, Sch Math & Stat, Xian 710071, Peoples R China
关键词: Convex programming;    Peaceman-Rachford splitting method;    Inertial proximal point;    Indefinite;    Variational inequality;    Global convergence;   
DOI  :  10.1016/j.cam.2020.112772
来源: Elsevier
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【 摘 要 】

We consider an inertial proximal strictly contractive Peaceman-Rachford splitting method (abbreviated as IPSCPRSM) with an indefinite proximal term for solving convex optimization problems with linear constraints. With the aid of variational inequality, proximal point method and fundamental inequality, we prove global convergence of the proposed method and analyze iteration complexity in the best function value and feasibility residues. The experimental results demonstrate the efficiency of the inertial extrapolation step and the indefinite proximal term even compared with the state-of-the-art methods. (C) 2020 Elsevier B.V. All rights reserved.

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