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Asymptotic Cones and Functions in Optimization and Variational Inequalities

Asymptotic Cones and Functions in Optimization and Variational Inequalities
Authors: Alfred Auslender, Marc Teboulle
Publisher: Springer
Category: Book

List Price: $109.00
Buy New: $34.59
You Save: $74.41 (68%)



New (10) Used (7) from $34.59

Sales Rank: 1826134

Media: Hardcover
Edition: 1
Number Of Items: 1
Pages: 272
Shipping Weight (lbs): 1
Dimensions (in): 9.3 x 6.2 x 0.8

ISBN: 0387955208
Dewey Decimal Number: 515.8
EAN: 9780387955209
ASIN: 0387955208

Publication Date: October 1, 2002
Availability: Usually ships in 1-2 business days

Also Available In:

  • Kindle Edition - Asymptotic Cones and Functions in Optimization and Variational Inequalities (Springer Monographs in Mathematics)
  • Digital - Asymptotic Cones and Functions in Optimization and Variational Inequalities (Springer Monographs in Mathematics)

Similar Items:

  • Numerical Optimization: Theoretical and Practical Aspects (Universitext)
  • Techniques of Variational Analysis (CMS Books in Mathematics)
  • Dynamic Programming and Optimal Control (2 Vol Set)
  • Convex Analysis and Nonlinear Optimization: Theory and Examples (CMS Books in Mathematics)
  • Numerical Optimization (Springer Series in Operations Research and Financial Engineering)

Editorial Reviews:

Product Description
This book provides a systematic and comprehensive account of asymptotic sets and functions from which a broad and useful theory emerges in the areas of optimization and variational inequalities. A variety of motivations leads mathematicians to study questions about attainment of the infimum in a minimization problem and its stability, duality and minmax theorems, convexification of sets and functions, and maximal monotone maps. For each there is the central problem of handling unbounded situations. Such problems arise in theory but also within the development of numerical methods.

The book focuses on the notions of asymptotic cones and associated asymptotic functions that provide a natural and unifying framework for the resolution of these types of problems. These notions have been used largely and traditionally in convex analysis, yet these concepts play a prominent and independent role in both convex and nonconvex analysis. This book covers convex and nonconvex problems, offering detailed analysis and techniques that go beyond traditional approaches.

The book will serve as a useful reference and self-contained text for researchers and graduate students in the fields of modern optimization theory and nonlinear analysis.


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