The authors prove that the •-optimal solutions of convex optimization problems are Lipschitz continuous with respect to data perturbations when these are measured in terms of the epi-distance. A similar property is obtained for the distance between the level sets of extended real valued functions. The authors also show that these properties imply that •-subgradient mapping is Lipschitz continuous.
