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

研究成果: 雜誌貢獻期刊論文同行評審

1   !!Link opens in a new tab 引文 斯高帕斯(Scopus)

摘要

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.

原文英語
頁(從 - 到)731-750
頁數20
期刊Journal of Industrial and Management Optimization
21
發行號1
DOIs
出版狀態已發佈 - 2025 1月

ASJC Scopus subject areas

  • 商業與國際管理
  • 策略與管理
  • 控制和優化
  • 應用數學

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