# Quadratic Programming and Affine Variational Inequalities

## A Qualitative Study

- 1 Citations
- 1 Mentions
- 14k Downloads

Part of the Nonconvex Optimization and Its Applications book series (NOIA, volume 78)

Advertisement

Book

- 1 Citations
- 1 Mentions
- 14k Downloads

Part of the Nonconvex Optimization and Its Applications book series (NOIA, volume 78)

This book develops a unified theory on qualitative aspects of nonconvex quadratic programming and affine variational inequalities. The first seven chapters introduce the reader step-by-step to the central issues concerning a quadratic program or an affine variational inequality, such as the solution existence, necessary and sufficient conditions for a point to belong to the solution set, and properties of the solution set. The subsequent two chapters briefly discuss two concrete models (a linear fractional vector optimization and a traffic equilibrium problem) whose analysis can benefit greatly from using the results on quadratic programs and affine variational inequalities. There are six chapters devoted to the study of continuity and differentiability properties of the characteristic maps and functions in quadratic programs and in affine variational inequalities where all the components of the problem data are subject to perturbation. Quadratic programs and affine variational inequalities under linear perturbations are studied in three other chapters.

One special feature of this book is that when a certain property of a characteristic map or function is investigated, the authors always try first to establish necessary conditions for it to hold, then they go on to study whether the obtained necessary conditions are sufficient ones. This helps to clarify the structures of the two classes of problems under consideration. The qualitative results can be used for dealing with algorithms and applications related to quadratic programming problems and affine variational inequalities.

*Audience*

This book is intended for graduate and postgraduate students in applied mathematics, as well as researchers in the fields of nonlinear programming and equilibrium problems. It can be used for some advanced courses on nonconvex quadratic programming and affine variational inequalities.

Optimality Conditions Vector optimization algorithms linear optimization optimization quadratic programming

- DOI https://doi.org/10.1007/b105061
- Copyright Information Springer Science+Business Media, Inc. 2005
- Publisher Name Springer, Boston, MA
- eBook Packages Mathematics and Statistics Mathematics and Statistics (R0)
- Print ISBN 978-0-387-24277-4
- Online ISBN 978-0-387-24278-1
- Series Print ISSN 1571-568X
- Buy this book on publisher's site