COMPLEXITY ANALYSIS OF LARGE-UPDATE INTERIOR-POINT METHODS FOR π“Ÿβˆ—(𝜿)-HLCP BASED ON A NEW PARAMETRIC KERNEL FUNCTION

This work proposes a primal-dual interior point technique for π’«βˆ—(πœ…)-Horizontal Linear Complementarity Problem (π’«βˆ—(πœ…)-HLCP), based on a novel parameterized kernel function. Our new eligible parametric kernel function’s feature produces the following iteration bound 𝑂(((𝑝+1)(𝑛𝑝)𝑝+22(𝑝+1)β„π‘™π‘œπ‘”(π‘›πœ€))) for the large-update method. Finally, we present numerical results demonstrating the algorithm’s pratical performance among various parameters.

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Publication Details

Journal
Statistics Optimization & Information Computing
Published
2025-04-24
DOI
https://doi.org/10.19139/soic-2310-5070-2345
Primary Topic
Mathematics and Applications
Type
article
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article

COMPLEXITY ANALYSIS OF LARGE-UPDATE INTERIOR-POINT METHODS FOR π“Ÿβˆ—(𝜿)-HLCP BASED ON A NEW PARAMETRIC KERNEL FUNCTION

Djeffal El Amir, Mokrani Ibtissam, Chalekh Randa
Statistics Optimization & Information Computing
Mathematics and Applications
article

COMPLEXITY ANALYSIS OF LARGE-UPDATE INTERIOR-POINT METHODS FOR π“Ÿβˆ—(𝜿)-HLCP BASED ON A NEW PARAMETRIC KERNEL FUNCTION

Djeffal El Amir, Mokrani Ibtissam, Chalekh Randa
article en

Abstract

This work proposes a primal-dual interior point technique for π’«βˆ—(πœ…)-Horizontal Linear Complementarity Problem (π’«βˆ—(πœ…)-HLCP), based on a novel parameterized kernel function. Our new eligible parametric kernel function’s feature produces the following iteration bound 𝑂(((𝑝+1)(𝑛𝑝)𝑝+22(𝑝+1)β„π‘™π‘œπ‘”(π‘›πœ€))) for the large-update method. Finally, we present numerical results demonstrating the algorithm’s pratical performance among various parameters.

Statistics Optimization & Information ComputingVol. 14(1)
University of Batna 1 (DZ)
Openalex Percentile: Top 79%
Mathematics and Applications
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