Unconstrained Nonlinear Programming

Gianni Di Pillo and Laura Palagi

ABSTRACT

In this article we consider the main classes of algorithms for the solution of unconstrained NLP problems. As a first step, we describe line-search techniques that are at the basis of most unconstrained algorithms. Then methods that use first- and second-order derivatives are reviewed. The last section is devoted to derivative-free methods. Far from being exhaustive, this article aims to give the main ideas and tools at the basis of unconstrained methods, and to suggest how to go more deeply into more technical and/or recent results.