Primal-dual proximal point algorithm for linearly constrained convex programming problems

DOI10.1007/BF00253807zbMath0767.90062OpenAlexW2053457083MaRDI QIDQ1203067

Masao Fukushima, Toshihide Ibaraki, Satoru Ibaraki

Publication date: 4 February 1993

Published in: Computational Optimization and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf00253807

zbMATH Keywords

separable problemsLagrangian functionnetwork flowproximal point algorithmlinearly constrained convex programmingapproximate saddle pointprimal-dual version

Mathematics Subject Classification ID

Convex programming (90C25) Deterministic network models in operations research (90B10) Computational methods for problems pertaining to operations research and mathematical programming (90-08)

Related Items

A proximal-based deomposition method for compositions method for convex minimization problems, Multi-step-prox-regularization method for solving convex variation problems, Unnamed Item

Uses Software

• NETGEN

Cites Work

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• NETGEN: A Program for Generating Large Scale Capacitated Assignment, Transportation, and Minimum Cost Flow Network Problems
• Monotone Operators and the Proximal Point Algorithm
• Augmented Lagrangians and Applications of the Proximal Point Algorithm in Convex Programming
• Convex Analysis