Relaxed augmented Lagrangian-based proximal point algorithms for convex optimization with linear constraints
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Publication:2438398
DOI10.3934/jimo.2014.10.743zbMath1292.65065OpenAlexW2315933830MaRDI QIDQ2438398
Wenxing Zhang, Yuan Shen, Bing-sheng He
Publication date: 11 March 2014
Published in: Journal of Industrial and Management Optimization (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.3934/jimo.2014.10.743
Numerical mathematical programming methods (65K05) Convex programming (90C25) Nonlinear programming (90C30) Numerical methods involving duality (49M29)
Related Items (3)
On non-ergodic convergence rate of the operator splitting method for a class of variational inequalities ⋮ A proximal point algorithm based on decomposition method for cone constrained multiobjective optimization problems ⋮ DISTRIBUTED PROXIMAL-GRADIENT METHOD FOR CONVEX OPTIMIZATION WITH INEQUALITY CONSTRAINTS
Uses Software
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