Bundle-based decomposition for large-scale convex optimization: Error estimate and application to block-angular linear programs

DOI10.1007/BF01581138zbMath0830.90120MaRDI QIDQ1338136

Deepankar Medhi

Publication date: 30 January 1996

Published in: Mathematical Programming. Series A. Series B (Search for Journal in Brave)

zbMATH Keywords

convex optimizationduality gaperror estimatebundle methodnonsmooth concave problem

Mathematics Subject Classification ID

Convex programming (90C25) Large-scale problems in mathematical programming (90C06) Linear programming (90C05)

Related Items (4)

Generalized proximal point algorithm for convex optimization ⋮ The Effect of Various Sparsity Structures on Parallelism and Algorithms to Reveal Those Structures ⋮ A cutting-plane approach for large-scale capacitated multi-period facility location using a specialized interior-point method ⋮ Iterative bundle-based decomposition for large-scale nonseparable convex optimization

Uses Software

• IMSL Numerical Libraries
• MINOS

Cites Work

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• Parallel bundle-based decomposition for large-scale structured mathematical programming problems
• DECOMP: an implementation of Dantzig-Wolfe decomposition for linear programming
• Decomposition Principle for Linear Programs
• Computational aspects of DYNAMICO : a model of trade and development in the world economy
• Computational experience with advanced implementation of decomposition algorithms for linear programming
• An advanced implementation of the Dantzig—Wolfe decomposition algorithm for linear programming
• Monotone Operators and the Proximal Point Algorithm
• A stable method for solving certain constrained least squares problems
• Validation of subgradient optimization
• Convex Analysis

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