An infeasible QP-free algorithm without a penalty function or a filter for nonlinear inequality-constrained optimization

In this paper, we present an infeasible quadratic programming-free method without using a penalty function or a filter for inequality-constrained optimization. At each iteration, three linear equations with the same coefficient matrix are solved. Furthermore, the nearly active set technique is used to reduce the amount of computational work. Under mild conditions, we prove that the proposed method has global and superlinear local convergence. At last, preliminary numerical results and comparison are reported.