A sub-quadratic programming feasible method for nonlinear programming

In this paper, a one-step superlinearly convergent feasible algorithm for nonlinear programming with nonlinear constraints is proposed. Since the iterative point generated by the algorithm is feasible and the algorithm only needs to solve a sub-quadratic programming and an inverse matrix, the new algorithm has some good properties for practical use. Under some milder conditions, the global convergence and local superlinear convergence are given in this paper.