An Interior-Point Algorithm for LCP Based on a Parameterized Hyperbolic Kernel Function
摘要
In this paper, we propose two new classes of kernel functions (KFs) with hyperbolic barrier terms and define interior-point methods (IPMs) based on these functions to solve linear complementarity problems (LCPs). The two proposed classes have similar forms but are different. One of them is a generalization, up to a multiplicative constant, to the KF recently introduced by Guerdouh et al. (J. Appl. Math. Comput. 1–19 (2023)). According to our analysis, the worst-case iteration complexity of large-update IPMs enjoys the best iteration bound