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COMPLEXITY ANALYSIS OF A PREDICTOR-CORRECTOR INTERIOR-POINT ALGORITHM FOR P∗(κ)-WEIGHTED LINEAR COMPLEMENTARITY PROBLEMS

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Abstract

This paper aims at a predictor-corrector interior-point algorithm for solving weighted linear complementarity problem with P(κ)-matrices, which is a variant of weighted complementarity problem and has wide applications in science, engineering, and economics. We first apply the algebraic equivalent transformation technique, and then use the identity function to determine the new search directions. Under suitable conditions, the feasibility and convergence of the algorithm are established. Moreover, we show that the proposed algorithm has polynomial-time complexity. As far as we know, this is the first predictor-corrector interior-point algorithm for P(κ)-weighted linear complementarity problem based on the above-mentioned search directions. Preliminary numerical results demonstrate that our algorithm performs well and efficiently on the test problems.

Original languageEnglish
Pages (from-to)731-750
Number of pages20
JournalJournal of Industrial and Management Optimization
Volume21
Issue number1
DOIs
Publication statusPublished - 2025 Jan

Keywords

  • P*(k)-weighted linear complementarity problem
  • Predictor-corrector interior-point algorithm
  • polynomial-time complexity
  • search direction

ASJC Scopus subject areas

  • Business and International Management
  • Strategy and Management
  • Control and Optimization
  • Applied Mathematics

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