Many current algorithms for nonlinear constrained optimization problems determine a search direction by solving a quadratic programming subproblem. The global convergence properties are addressed by using a line search technique and a merit function to modify the length of the step obtained from the quadratic program. In unconstrained optimization, trust region strategies have been very successful. In this thesis we present a new approach for equality constrained optimization problems based on a trust region strategy. The direction selected is not necessarily the solution of the standard quadratic programming subproblem.