Application of a smoothing technique to decomposition in convex optimization

Dual decomposition is a powerful technique for deriving decomposition schemes for convex optimization problems with specific structure. Although the Augmented Lagrangian is computationally more stable than the ordinary Lagrangian, the \textit{prox-term} destroys the separability of the given problem. In this paper we use another approach to obtain a smooth Lagrangian, based on a smoothing technique … Read more