A full-Newton step infeasible interior-point method based on a trigonometric kernel function without centering steps

In this paper, a full-Newton step infeasible interior-point method for solving linear optimization problems is presented. In each iteration, the algorithm uses only one so-called feasibility step and computes the feasibility search directions by using a trigonometric kernel function with a double barrier term. Convergence of the algorithm is proved and it is shown that the complexity bound of the algorithm matches the currently best known iteration bound for infeasible interior-point methods. Finally, some numerical results are provided to illustrate the performance of the proposed algorithm.