A QP-free algorithm without a penalty function and a filter for nonlinear constrained optimization

In this paper, we propose a new QP-free method without using a penalty function and a filter for nonlinear constrained optimization. This algorithm needs to solve five systems of linear equations having the same coefficient matrix per iteration. We prove that the algorithm is convergent to a KKT point. Furthermore, the nearly active set technique is used to improve the computational effect. Under mild conditions, we prove that the proposed method has global and superlinear local convergence. At last, some preliminary numerical results are reported.