On the augmented subproblems within sequential methods for nonlinear programming

In the context of sequential methods for solving general nonlinear programming problems, it is usual to work with augmented subproblems instead of the original ones. This paper addresses the theoretical reasoning behind handling the original subproblems by an augmentation strategy related to the differentiable reformulation of the $$\ell _1$$ ℓ1 -penalized problem. Nevertheless, this paper is not concerned with the sequential method itself, but with the features about the original problem that can be inferred from the properties of the solution of the augmented problem. Moreover, no assumption is made upon the feasibility of the original problem, neither about the fulfillment of any constraint qualification, nor of any regularity condition, such as calmness. The convergence analysis of the involved sequences is presented, independent of the strategy employed to produce the iterates. Examples that elucidate the interrelations among the obtained results are also provided.