A predictor-corrector interior-point algorithm for $ P_{*}(\kappa) $-weighted linear complementarity problems
In this paper, we present a predictor-corrector interior-point algorithm for $ P_{*}(\kappa) $-weighted linear complementarity problems. Based on the kernel function $ \varphi(t) = \sqrt{t} $, the search direction of the algorithm is obtained. By choosing appropriate parameters, we prove that the al...
| 出版年: | AIMS Mathematics |
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| 主要な著者: | , , , |
| フォーマット: | 論文 |
| 言語: | 英語 |
| 出版事項: |
AIMS Press
2023-02-01
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| 主題: | |
| オンライン･アクセス: | https://www.aimspress.com/article/doi/10.3934/math.2023462?viewType=HTML |
| 要約: | In this paper, we present a predictor-corrector interior-point algorithm for $ P_{*}(\kappa) $-weighted linear complementarity problems. Based on the kernel function $ \varphi(t) = \sqrt{t} $, the search direction of the algorithm is obtained. By choosing appropriate parameters, we prove that the algorithm is feasible and convergent. It is shown that the proposed algorithm has polynomial iteration complexity. Numerical results illustrate the effectiveness of the algorithm. |
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| ISSN: | 2473-6988 |