Aspects of Semidefinite Programming

Interior Point Algorithms and Selected Applications
1. Auflage. Softcover version of original hardcover Auflage 2002
ISBN: 978-1-4419-5216-5
Verlag: Springer US

Buch, Englisch, Band 65, 288 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 470 g

Reihe: Applied Optimization

Semidefinite programming has been described as linear programming for the year 2000. It is an exciting new branch of mathematical programming, due to important applications in control theory, combinatorial optimization and other fields. Moreover, the successful interior point algorithms for linear programming can be extended to semidefinite programming.
In this monograph the basic theory of interior point algorithms is explained. This includes the latest results on the properties of the central path as well as the analysis of the most important classes of algorithms. Several "classic" applications of semidefinite programming are also described in detail. These include the Lovász theta function and the MAX-CUT approximation algorithm by Goemans and Williamson.
Audience: Researchers or graduate students in optimization or related fields, who wish to learn more about the theory and applications of semidefinite programming.

Zielgruppe

Research

Autoren/Hrsg.

de Klerk, E.

Fachgebiete

• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Programmierung: Methoden und Allgemeines
• Mathematik | Informatik Mathematik Algebra Elementare Algebra
• Mathematik | Informatik Mathematik Operations Research Spieltheorie
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Computeranwendungen in der Mathematik
• Mathematik | Informatik EDV | Informatik Informatik Logik, formale Sprachen, Automaten
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Numerische Mathematik

Inhaltsverzeichnis

Theory and Algorithms.- Duality, Optimality, and Degeneracy.- The Central Path.- Self-Dual Embeddings.- The Primal Logarithmic Barrier Method.- Primal-Dual Affine-Scaling Methods.- Primal-Dual Path-Following Methods.- Primal-Dual Potential Reduction Methods.- Selected Applications.- Convex Quadratic Approximation.- The Lovász ?-Function.- Graph Coulouring and the Max-K-Cut Problem.- The Stability Number of a Graph and Standard Quadratic Optimization.- The Satisfiability Problem.