On Karmakar's Algorithm for Linear Programming

This paper deals with the convergence of the new polynomial-time algorithm developed by N.Karmakar and its relationship with thickness of concentric ellipsoids. Herein, we generalize the Karmakar'sinequality to discuss the bounds of objective function and obtain refind form of Karmakar's Formula for thespeed of convergence and convergence ration Karmakar's algorithm admits linear convergence in general andsupper linear convergence in special case which hopelessly turn out to be trivial. We also show the super linearconvergence of the sequence of the values of the objective function at different points of the polytope

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-08-09
DOI
https://doi.org/10.5281/zenodo.16785173
Primary Topic
Advanced Optimization Algorithms Research
Type
article
Field-Weighted Citation Impact
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article

On Karmakar's Algorithm for Linear Programming

Zenodo (CERN European Organization for Nuclear Research)
Advanced Optimization Algorithms Research
article

On Karmakar's Algorithm for Linear Programming

article en

Abstract

This paper deals with the convergence of the new polynomial-time algorithm developed by N.Karmakar and its relationship with thickness of concentric ellipsoids. Herein, we generalize the Karmakar'sinequality to discuss the bounds of objective function and obtain refind form of Karmakar's Formula for thespeed of convergence and convergence ration Karmakar's algorithm admits linear convergence in general andsupper linear convergence in special case which hopelessly turn out to be trivial. We also show the super linearconvergence of the sequence of the values of the objective function at different points of the polytope

Zenodo (CERN European Organization for Nuclear Research)
Bir Hospital (NP), Biratnagar Eye Hospital (NP), Mid-West University (NP)
Openalex Percentile: Top 44%
Advanced Optimization Algorithms Research
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