Computation of condition numbers for linear programming problems using Peña’s method

DOI10.1080/10556780500098599zbMath1136.90540OpenAlexW2067017139MaRDI QIDQ5475283

Kim-Chuan Toh, Joo-Siong Chai

Publication date: 16 June 2006

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

Full work available at URL: https://doi.org/10.1080/10556780500098599

zbMATH Keywords

complexitylinear programminginterior-point methodsconic optimizationrenegar condition number

Mathematics Subject Classification ID

Applications of mathematical programming (90C90) Interior-point methods (90C51)

Related Items

Behavioral measures and their correlation with IPM iteration counts on semi-definite programming problems, A hybrid branch-and-bound approach for exact rational mixed-integer programming

Uses Software

• LOQO
• AMPL
• NETLIB LP Test Set

Cites Work

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• Some perturbation theory for linear programming
• Computing approximate solutions for convex conic systems of constraints
• Two properties of condition numbers for convex programs via implicitly defined barrier functions
• Linear programming, complexity theory and elementary functional analysis
• Some characterizations and properties of the ``distance to the ill-posedness and the condition measure of a conic linear system
• A New Condition Measure, Preconditioners, and Relations Between Different Measures of Conditioning for Conic Linear Systems
• Self-Scaled Barriers and Interior-Point Methods for Convex Programming
• Computational Experience and the Explanatory Value of Condition Measures for Linear Optimization
• LOQO user's manual — version 3.10
• Understanding the Geometry of Infeasible Perturbations of a Conic Linear System