The rate of convergence of proximal method of multipliers for nonlinear programming

DOI10.1080/10556788.2020.1738435zbMath1464.90104OpenAlexW3010660210MaRDI QIDQ5858993

Yu-Le Zhang, Jia Wu, Li-wei Zhang

Publication date: 15 April 2021

Published in: Optimization Methods and Software (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10556788.2020.1738435

zbMATH Keywords

rate of convergencestrict complementaritynonlinear programmingproximal method of multipliers

Mathematics Subject Classification ID

Nonlinear programming (90C30)

Related Items (1)

Perturbed augmented Lagrangian method framework with applications to proximal and smoothed variants

Cites Work

• The augmented Lagrangian method for equality and inequality constraints in Hilbert spaces
• The rate of convergence of the augmented Lagrangian method for nonlinear semidefinite programming
• Extended convergence results for the method of multipliers for nonstrictly binding inequality constraints
• Multiplier and gradient methods
• The multiplier method of Hestenes and Powell applied to convex programming
• A Globally Convergent Augmented Lagrangian Algorithm for Optimization with General Constraints and Simple Bounds
• Monotone Operators and the Proximal Point Algorithm
• Augmented Lagrangians and Applications of the Proximal Point Algorithm in Convex Programming
• A dual approach to solving nonlinear programming problems by unconstrained optimization
• Definite and Semidefinite Quadratic Forms
• Some new bounds for singular values and eigenvalues of matrix products
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