## An interior point method for general nonlinear programming using trust regions

In this talk we describe ongoing work on an interior point method for general nonlinearly constrained optimization. Our approach is a primal dual method related to those used successfully in linear and convex programming, but is based in part on the trust region method for equality con strained optimization due to Byrd and Omojokun, and developed further by Nocedal and Plantenga. This allows us to use an indefinite Hessian matrix based on exact second derivatives or approximations. Such an approach is expected to be most effective when satisfaction of nonlinear constraints is a major issue. We describe the operation ofmore »