Discrete Gradient Methods

Abstract

In this chapter, we introduce two discrete gradient methods that can be considered as semi-derivative free methods in a sense that they do not use subgradient information and they do not approximate the subgradient but at the end of the solution process (i.e., near the optimal point). The introduced methods are the original discrete gradient method for small-scale nonsmooth optimization and its limited memory bundle version the limited memory discrete gradient bundle method for medium- and semi-large problems.