Primal-dual interior-point algorithm for linearly constrained convex optimization based on a parametric algebraic transformation

Fuente: arXiv
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Main Authors: Kraria, Aicha, Merikhi, Bachir, Benterki, Djamel
Format: Preprint
Published: 2024
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author Kraria, Aicha
Merikhi, Bachir
Benterki, Djamel
author_facet Kraria, Aicha
Merikhi, Bachir
Benterki, Djamel
contents In this paper, we present an interior point algorithm with a full-Newton step for solving a linearly constrained convex optimization problem, in which we propose a generalization of the work of Kheirfam and Nasrollahi \cite{kheirfam2018full}, that consists in determining the descent directions through a parametric algebraic transformation. The work concludes with a complete study of the convergence of the algorithm and its complexity, where we show that the obtained algorithm achieves a polynomial complexity bounds.
format Preprint
id arxiv_https___arxiv_org_abs_2403_11684
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Primal-dual interior-point algorithm for linearly constrained convex optimization based on a parametric algebraic transformation
Kraria, Aicha
Merikhi, Bachir
Benterki, Djamel
Numerical Analysis
Optimization and Control
In this paper, we present an interior point algorithm with a full-Newton step for solving a linearly constrained convex optimization problem, in which we propose a generalization of the work of Kheirfam and Nasrollahi \cite{kheirfam2018full}, that consists in determining the descent directions through a parametric algebraic transformation. The work concludes with a complete study of the convergence of the algorithm and its complexity, where we show that the obtained algorithm achieves a polynomial complexity bounds.
title Primal-dual interior-point algorithm for linearly constrained convex optimization based on a parametric algebraic transformation
topic Numerical Analysis
Optimization and Control
url https://arxiv.org/abs/2403.11684