  Algencan is a well established safeguarded Augmented Lagrangian algorithm
introduced in [R. Andreani, E. G. Birgin, J. M. Mart\'{\i}nez and M. L.
Schuverdt, On Augmented Lagrangian methods with general lower-level
constraints, SIAM Journal on Optimization 18, pp. 1286-1309, 2008]. Complexity
results that report its worst-case behavior in terms of iterations and
evaluations of functions and derivatives that are necessary to obtain suitable
stopping criteria are presented in this work. In addition, the computational
performance of a new version of the method is presented, which shows that the
updated software is a useful tool for solving large-scale constrained
optimization problems.
