New search direction based on a class of parametric kernel functions with a Full Newton step Infeasible O(nL) Interior point Methods for Linear Optimization

  • BOUALI Samir Dr.
DOI: https://doi.org/10.19139/soic-2310-5070-3076
Keywords: Linear programming, Infeasible interior-point method, Full-Newton step, Polynomial complexity, Kernel function

Abstract

In this paper which is inspired by the work of Roos [7] (SIAM J. Optim. 16(4):1110-1136, 2006), we analysed a new search direction based on a class of parametric kernel functions for IIPMs algorithms. The main iteration of the algorithm consists of a feasibility step and several centrality steps. The neighborhood of Newton process is more wider using a sharper quadratic convergence results. The complexity is polynomial and coincides with the currently best known iteration bound based on centrality steps.
Published
2026-02-04
How to Cite
Samir, B. (2026). New search direction based on a class of parametric kernel functions with a Full Newton step Infeasible O(nL) Interior point Methods for Linear Optimization. Statistics, Optimization & Information Computing. https://doi.org/10.19139/soic-2310-5070-3076
Issue
Online First
Section
Research Articles
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