A proximal fully parallel splitting method with a relaxation factor for separable convex programming

In this paper, we propose a proximal fully parallel splitting method with a relaxation factor for solving separable convex minimization model with linear constraints, where the objective function is the sum of m individual functions without coupled variables. With a full Jacobian decomposition, we d...

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Veröffentlicht in:	Applied numerical mathematics Jg. 195; S. 17 - 38
Hauptverfasser:	Yin, Jianghua, Jian, Jinbao, Jiang, Xianzhen, Wu, Jiansheng, Ma, Guodong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.01.2024
Schlagworte:	Augmented Lagrangian method Convergence rate Relaxation factor Splitting algorithm Step size Step size Splitting algorithm Convergence rate Augmented Lagrangian method Relaxation factor
ISSN:	0168-9274
Online-Zugang:	Volltext
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