Convex analysis and global optimization /

Convex analysis and global optimization /

Saved in:

Bibliographic Details
Author / Creator:	Tuy, Hoang.
Edition:	Second edition.
Imprint:	Switzerland : Springer, 2016.
Description:	1 online resource
Language:	English
Series:	Springer optimization and its applications ; volume 110 Springer optimization and its applications ; v. 110.
Subject:	Convex functions. Convex sets. Mathematical optimization. Nonlinear programming. Convex functions. Convex sets. Mathematical optimization. Nonlinear programming.
Format:	E-Resource Book
URL for this record:	http://pi.lib.uchicago.edu/1001/cat/bib/11267742

Hidden Bibliographic Details
ISBN:	9783319314846 331931484X 9783319314822 3319314823
Notes:	Includes bibliographical references and index. Print version record.
Summary:	This book presents state-of-the-art results and methodologies in modern global optimization, and has been a staple reference for researchers, engineers, advanced students (also in applied mathematics), and practitioners in various fields of engineering. The second edition has been brought up to date and continues to develop a coherent and rigorous theory of deterministic global optimization, highlighting the essential role of convex analysis. The text has been revised and expanded to meet the needs of research, education, and applications for many years to come. Updates for this new edition include: · Discussion of modern approaches to minimax, fixed point, and equilibrium theorems, and to nonconvex optimization; · Increased focus on dealing more efficiently with ill-posed problems of global optimization, particularly those with hard constraints;
Other form:	Print version: Tuy, Hoang. Convex analysis and global optimization. Second edition 2016. [Place of publication not identified] : Springer, 2016 3319314823

Table of Contents:

1. Convex Sets
2. Convex Functions
3. Fixed Point and Equilibrium
4. DC Functions and DC Sets
5. Motivation and Overview
6. General Methods
7. DC Optimization Problems
8. Special Methods
9. Parametric Decomposition
10. Nonconvex Quadratic Programming
11. Monotonic Optimization
12. Polynomial Optimization
13. Optimization Under Equilibrium Constraints
References
Index.