Kernel-Based Full-Newton Step Feasible Interior-Point Algorithm for P(κ) -Weighted Linear Complementarity Problem

Xiaoni Chi, Guoqiang Wang, Goran Lesaja

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

In this paper, we consider a kernel-based full-Newton step feasible interior-point method (IPM) for P(κ)-Weighted Linear Complementarity Problem (WLCP). The specific eligible kernel function is used to define an equivalent form of the central path, the proximity measure, and to obtain search directions. Full-Newton steps are adopted to avoid the line search at each iteration. It is shown that with appropriate choices of the parameters, and a certain condition on the starting point, the iterations always lie in the defined neighborhood of the central path. Assuming strict feasibility of P(κ)-WLCP, it is shown that the IPM converges to the ε-approximate solution of P(κ)-WLCP in a polynomial number of iterations. Few numerical results are provided to indicate the computational performance of the algorithm.

Original languageEnglish
Pages (from-to)108-132
Number of pages25
JournalJournal of Optimization Theory and Applications
Volume202
Issue number1
DOIs
StatePublished - Nov 16 2023

Keywords

  • Full-Newton step
  • Interior-point algorithm
  • Polynomial complexity
  • P∗(κ)-weighted linear complementarity problem

Fingerprint

Dive into the research topics of 'Kernel-Based Full-Newton Step Feasible Interior-Point Algorithm for P(κ) -Weighted Linear Complementarity Problem'. Together they form a unique fingerprint.

Cite this