Implementing proximal point methods for linear programming

DOI10.1007/BF00939565zbMath0676.90042OpenAlexW2084123115MaRDI QIDQ1123124

Stephen J. Wright

Publication date: 1990

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

Full work available at URL: https://doi.org/10.1007/bf00939565

zbMATH Keywords

proximal point methodsmethod of multipliersConvergence resultstwo-metric gradient-projection approachweakly convex quadratic program

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Linear programming (90C05)

Related Items

Alternating direction method of multipliers for linear programming, Proximal minimizations with \(D\)-functions and the massively parallel solution of linear network programs, Zonotopes and the LP-Newton method, A characterization of the optimal set of linear programs based on the augmented lagrangian, A continuation method for monotone variational inequalities, Generalized proximal point algorithm for convex optimization, Reconstruction of sparse signals in impulsive disturbance environments, PAL-Hom method for QP and an application to LP, Perturbed proximal primal-dual algorithm for nonconvex nonsmooth optimization, An Asymptotically Superlinearly Convergent Semismooth Newton Augmented Lagrangian Method for Linear Programming, A Subspace Modified PRP Method for Large-scale Nonlinear Box-Constrained Optimization, Primal-dual proximal point algorithm for linearly constrained convex programming problems, A primal-dual regularized interior-point method for convex quadratic programs, A primal-dual proximal point algorithm for constrained convex programs, Projected Barzilai-Borwein methods for large-scale box-constrained quadratic programming, Further study on augmented Lagrangian duality theory, On a gradient-based algorithm for sparse signal reconstruction in the signal/measurements domain, Modulus-Type Inner Outer Iteration Methods for Nonnegative Constrained Least Squares Problems, The adventures of a simple algorithm, Augmented Lagrangian algorithms for linear programming

Uses Software

• MINOS

Cites Work

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