An asymmetric proximal decomposition method for convex programming with linearly coupling constraints

DOI10.1155/2012/281396zbMath1246.90117OpenAlexW2071926927WikidataQ58698812 ScholiaQ58698812MaRDI QIDQ447556

J. Herrera, D. Rodríguez-Gómez

Publication date: 4 September 2012

Published in: Advances in Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2012/281396

Mathematics Subject Classification ID

Convex programming (90C25) Variational inequalities (49J40)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Proximal-point algorithm using a linear proximal term
• Application of the alternating direction method of multipliers to separable convex programming problems
• A logarithmic-quadratic proximal method for variational inequalities
• Proximal minimization algorithm with \(D\)-functions
• A proximal-based deomposition method for compositions method for convex minimization problems
• Self-adaptive operator splitting methods for monotone variational inequalities
• Comparison of two kinds of prediction-correction methods for monotone variational inequalities
• A modified augmented Lagrangian method for a class of monotone variational inequalities
• Separable diagonalized multiplier method for decomposition nonlinear programs
• Generalized Linear-Quadratic Problems of Deterministic and Stochastic Optimal Control in Discrete Time
• Applications of a Splitting Algorithm to Decomposition in Convex Programming and Variational Inequalities
• Monotone Operators and the Proximal Point Algorithm
• Augmented Lagrangians and Applications of the Proximal Point Algorithm in Convex Programming
• Numerical Optimization
• Alternating Projection-Proximal Methods for Convex Programming and Variational Inequalities
• Convergence of Proximal-Like Algorithms
• Proximal Decomposition on the Graph of a Maximal Monotone Operator