
Nonlinear Optimization
Lectures given at the C.I.M.E. Summer School held in Cetraro, Italy, July 1-7, 2007
Springer (Publisher)
Published on 24. March 2010
Book
Paperback/Softback
XIII, 279 pages
978-3-642-11338-3 (ISBN)
Description
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.
More details
Series
Edition
2010 ed.
Language
English
Place of publication
Berlin
Germany
Publishing group
Springer Berlin
Target group
Professional and scholarly
Research
Illustrations
XIII, 279 p.
Dimensions
Height: 23.5 cm
Width: 15.5 cm
Weight
950 gr
ISBN-13
978-3-642-11338-3 (9783642113383)
DOI
10.1007/978-3-642-11339-0
Schweitzer Classification
Content
Global Optimization: A Quadratic Programming Perspective.- Nonsmooth Optimization.- The Sequential Quadratic Programming Method.- Interior Point Methods for Nonlinear Optimization.