Enlarging neighborhoods of interior-point algorithms for linear programming via least values of proximity measure functions

DOI10.1016/j.apnum.2006.09.009zbMath1121.65072OpenAlexW2113292332MaRDI QIDQ997220

Publication date: 23 July 2007

Published in: Applied Numerical Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.apnum.2006.09.009

zbMATH Keywords

linear programming interior-point algorithms quadratic convergence predictor-corrector methods iteration complexity neighborhoods

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Linear programming (90C05) Interior-point methods (90C51)

Cites Work

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Complexity of Predictor-Corrector Algorithms for LCP Based on a Large Neighborhood of the Central Path
On the Local Convergence of a Predictor-Corrector Method for Semidefinite Programming
The complexity of high-order predictor-corrector methods for solving sufficient linear complementarity problems
A Predictor-Corrector Algorithm for Linear Optimization Based on a Specific Self-Regular Proximity Function

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