Abstract: In this work we propose a primal-dual algorithm for the solution of equality constrained optimization problems with bounded variables. The core of the method is a local algorithm, wich relies on a truncated scheme for the computation of a search direction in the product space of the problem variables and of the multipliers associated with the equality constraints. The local algorithm is globalized by means of a mixed penalty augmented lagrangian merit function, where the bound constraints are treated by an exact penalty approach and the equality constraints are treated by an exact augmented Lagrangian approach. The resulting algorithm is globally and superlinearly convergent under mild assumptions. Due to the theoretical properties of the exact merit function, the algorithm can be fruitfully employed to search for
global solutions of constrained problems.