This volume presents recent advances in continuous optimization; it is authored by four well-known experts in the field and presents classical as well as advanced material on currently active research areas, such as: the family of Sequential Quadratic Programming methods for local constrained optimization, the study of Global Optimization by means of (non-convex) standard quadratic problems, Nonsmooth Optimization, and recent advances in Interior Point Methods for nonlinear optimization. The book is intended as a reference work for advanced research in the field of optimization theory and methods.

Klappentext

This volume collects the expanded notes of four series of lectures given on the occasion of the CIME course on Nonlinear Optimization held in Cetraro, Italy, from July 1 to 7, 2007. The Nonlinear Optimization problem of main concern here is the problem n of determining a vector of decision variables x ? R that minimizes (ma- n mizes) an objective function f(·): R ? R,when x is restricted to belong n to some feasible setF? R , usually described by a set of equality and - n n m equality constraints: F = {x ? R : h(x)=0,h(·): R ? R ; g(x) ? 0, n p g(·): R ? R }; of course it is intended that at least one of the functions f,h,g is nonlinear. Although the problem canbe stated in verysimpleterms, its solution may result very di?cult due to the analytical properties of the functions involved and/or to the number n,m,p of variables and constraints. On the other hand, the problem has been recognized to be of main relevance in engineering, economics, and other applied sciences, so that a great lot of e?ort has been devoted to develop methods and algorithms able to solve the problem even in its more di?cult and large instances. The lectures have been given by eminent scholars, who contributed to a great extent to the development of Nonlinear Optimization theory, methods and algorithms. Namely, they are: - Professor Immanuel M.

Inhalt

Global Optimization: A Quadratic Programming Perspective.- Nonsmooth Optimization.- The Sequential Quadratic Programming Method.- Interior Point Methods for Nonlinear Optimization.