Some properties of generalized proximal point methods for quadratic and linear programming

DOI10.1007/BF02193058zbMath0831.90092MaRDI QIDQ1896573

Alfredo Noel Iusem

Publication date: 4 September 1995

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

zbMATH Keywords

convex optimizationproximal point methodBregman functions

Mathematics Subject Classification ID

Quadratic programming (90C20) Linear programming (90C05)

Related Items (16)

A note on the existence of zeroes of convexly regularized sums of maximal monotone operators ⋮ Proximal Methods with Penalization Effects in Banach Spaces ⋮ A proximal method with logarithmic barrier for nonlinear complementarity problems ⋮ Equilibrium programming using proximal-like algorithms ⋮ On some properties of generalized proximal point methods for variational inequalities ⋮ Dynamic non-diagonal regularization in interior point methods for linear and convex quadratic programming ⋮ Re-examination of Bregman functions and new properties of their divergences ⋮ Newton-type Methods with Generalized Distances For Constrained Optimization ⋮ Proximal-like algorithm using the quasi D-function for convex second-order cone programming ⋮ A generalized proximal-point-based prediction-correction method for variational inequality problems ⋮ On inexact generalized proximal methods with a weakened error tolerance criterion ⋮ INEXACT VERSIONS OF PROXIMAL POINT AND AUGMENTED LAGRANGIAN ALGORITHMS IN BANACH SPACES ⋮ On a generalized proximal point method for solving equilibrium problems in Banach spaces ⋮ Dual convergence of the proximal point method with Bregman distances for linear programming ⋮ An interior point-proximal method of multipliers for convex quadratic programming ⋮ Inexact proximal point algorithms and descent methods in optimization

Cites Work

• On the convergence of the exponential multiplier method for convex programming
• Multiplicative iterative algorithms for convex programming
• A new polynomial-time algorithm for linear programming
• A relaxed version of Bregman's method for convex programming
• Proximal minimization algorithm with \(D\)-functions
• On the convergence rate of entropic proximal optimization methods
• Limiting behavior of the affine scaling continuous trajectories for linear programming problems
• Convergence Analysis of a Proximal-Like Minimization Algorithm Using Bregman Functions
• Monotone Operators and the Proximal Point Algorithm
• Nonlinear Proximal Point Algorithms Using Bregman Functions, with Applications to Convex Programming
• Entropy-Like Proximal Methods in Convex Programming
• Convergence Rate Analysis of Nonquadratic Proximal Methods for Convex and Linear Programming
• Convex Analysis
• Limiting Behavior of Trajectories Generated by a Continuation Method for Monotone Complementarity Problems
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