An infeasible interior-point algorithm for monotone linear complementarity problem based on a specific kernel function

In this paper, a full-Newton step infeasible kernel-based interior-point algorithm for solving monotone linear complementarity problems is proposed. In each iteration, the algorithm computes the new feasibility search directions by using a specific kernel function with the trigonometric barrier term and obtains the centering search directions using the classical kernel function. The algorithm takes only full-Newton steps and therefore no line-searches are needed for generating the new iterations. The convergence of the algorithm is shown and it is proved that the iteration bound of the algorithm coincides with the currently best iteration bound for monotone linear complementarity problem.