A Newton descent logarithmic barrier interior-point algorithm for monotone LCP

\nThe growing importance of the monotone linear complementarity problems (LCP) lies in the different applications it covers, both in mathematics and in practice. In this paper, based on the optimization techniques, we propose a descent logarithmic barrier interior-point method for solving the (LCP). The idea is to transform the LCP into an equivalent convex quadratic optimization problem, denoted by (CQO). Then, the associated barrier problem to CQO is formulated. The existence and the uniqueness of optimal solution of the barrier problem is showed. For its numerical aspects, the descent direction is computed by using the classical Newton’s method. However, to determine the displacement step along this direction, guaranteeing the maintenance of the new iterates inside the domain during the algorithm process and the improvement of the value of the objective function, we apply a new approach using approximation functions known as “minorant and majorant approximating functions”. The numerical results obtained are very promising and show the effectiveness of this new strategy.\n

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2024-12-24
DOI
https://doi.org/10.1051/ro/2024216/pdf
Primary Topic
Advanced Optimization Algorithms Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Newton descent logarithmic barrier interior-point algorithm for monotone LCP

Springer Link (Chiba Institute of Technology)
Advanced Optimization Algorithms Research
article

A Newton descent logarithmic barrier interior-point algorithm for monotone LCP

article en

Abstract

\nThe growing importance of the monotone linear complementarity problems (LCP) lies in the different applications it covers, both in mathematics and in practice. In this paper, based on the optimization techniques, we propose a descent logarithmic barrier interior-point method for solving the (LCP). The idea is to transform the LCP into an equivalent convex quadratic optimization problem, denoted by (CQO). Then, the associated barrier problem to CQO is formulated. The existence and the uniqueness of optimal solution of the barrier problem is showed. For its numerical aspects, the descent direction is computed by using the classical Newton’s method. However, to determine the displacement step along this direction, guaranteeing the maintenance of the new iterates inside the domain during the algorithm process and the improvement of the value of the objective function, we apply a new approach using approximation functions known as “minorant and majorant approximating functions”. The numerical results obtained are very promising and show the effectiveness of this new strategy.\n

Springer Link (Chiba Institute of Technology)
Openalex Percentile: Top 52%
Advanced Optimization Algorithms Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.