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A modified Full-Newton Step Infeasible interior-Point Algorithm for Linear Optimization

We present a full-Newton step infeasible interior-point algorithm based on a new search direction. The algorithm decreases the duality gap and the feasibility residuals at the same rate. During this algorithm we construct strictly feasible iterates for a sequence of perturbations of the given problem and its dual problem. Each main iteration of the algorithm consists of a feasibility step and some centering steps. We show that the algorithm converges and finds an approximate solution in a polynomial time complexity. A numerical study is done for its numerical performance.