A convergent decomposition method for box-constrained optimization problems

DOI10.1007/s11590-009-0119-8zbMath1170.90485OpenAlexW2008698372MaRDI QIDQ839804

Andrea Cassioli, Marco Sciandrone

Publication date: 3 September 2009

Published in: Optimization Letters (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/2158/388516

zbMATH Keywords

global convergencedecomposition methodsGauss-southwell method

Mathematics Subject Classification ID

Nonlinear programming (90C30)

Related Items (3)

The 2-coordinate descent method for solving double-sided simplex constrained minimization problems ⋮ A feasible decomposition method for constrained equations and its application to complementarity problems ⋮ On the convergence of a Jacobi-type algorithm for singly linearly-constrained problems subject to simple bounds

Uses Software

• TRON

Cites Work

• An algorithm for a singly constrained class of quadratic programs subject upper and lower bounds
• A coordinate gradient descent method for nonsmooth separable minimization
• Decomposition algorithm model for singly linearly-constrained problems subject to lower and Upper bounds
• Algorithms for bound constrained quadratic programming problems
• On the convergence of the coordinate descent method for convex differentiable minimization
• On the convergence of the block nonlinear Gauss-Seidel method under convex constraints
• Downlink beamforming for DS-CDMA mobile radio with multimedia services
• Newton's Method for Large Bound-Constrained Optimization Problems
• A Truncated Newton Algorithm for Large Scale Box Constrained Optimization
• A simple decomposition method for support vector machines
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