Kernel-Based Full-Newton Step Feasible Interior-Point Algorithm for P_*(κ ) -Weighted Linear Complementarity Problem

Journal of Optimization Theory and Applications(2023)

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摘要
In this paper, we consider a kernel-based full-Newton step feasible interior-point method (IPM) for P_*(κ ) -Weighted Linear Complementarity Problem (WLCP). The specific eligible kernel function is used to define an equivalent form of the central path, the proximity measure, and to obtain search directions. Full-Newton steps are adopted to avoid the line search at each iteration. It is shown that with appropriate choices of the parameters, and a certain condition on the starting point, the iterations always lie in the defined neighborhood of the central path. Assuming strict feasibility of P_*(κ ) -WLCP, it is shown that the IPM converges to the ε -approximate solution of P_*(κ ) -WLCP in a polynomial number of iterations. Few numerical results are provided to indicate the computational performance of the algorithm.
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关键词
P_*(κ ) -weighted linear complementarity problem,Interior-point algorithm,Full-Newton step,Polynomial complexity
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