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A novel corrector-predictor interior-point algorithm for P*(κ)-weighted linear complementarity problems based on an AET function
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DOI：10.1080/02331934.2026.2642344.png)
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Abstract
En 中文
This paper considers $ P_{*}(\kappa ) $ P & lowast;(kappa)-Weighted Linear Complementarity Problems (WLCPs) and gives a novel corrector-predictor interior-point algorithm (IPA) based on an algebraic equivalent transformation function. The strict feasibility and convergence of our proposed method for $ P_{*}(\kappa ) $ P & lowast;(kappa)-WLCP are established. In particular, we demonstrate that the iteration bound of the algorithm enjoys a polynomial complexity bound, which is comparable to the best available one for such existing IPAs. Finally, the proposed corrector-predictor IPA is applied to a small set of numerical examples to support the viability and efficiency of the algorithm and illustrate potential for the efficient implementation.
Keywords:
Weighted linear complementarity problems
interior-point algorithm
AET function
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1.8
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