Title: A brief overview of trust region interior point methods for nonlinear programming
Presentation Slides


In this talk I will present a brief overview of trust region interior point methods for nonlinear programming including a new primal-dual algorithm for the minimization of non-convex objective functions subject to general inequality and linear equality constraints. The method uses a primal-dual trust-region model to ensure descent on a suitable merit function. Convergence is proved to second-order critical points from arbitrary starting points. Preliminary numerical results are very encouraging. Rather than go into details of the proofs I will try and present the motivation and basic ideas behind both the algorithms and the theory.