Interior Point Algorithms and Selected Applications
First Statement of Responsibility
by Etienne Klerk.
.PUBLICATION, DISTRIBUTION, ETC
Place of Publication, Distribution, etc.
Boston, MA
Name of Publisher, Distributor, etc.
Springer US
Date of Publication, Distribution, etc.
2004
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
(xvi, 288 pages).
SERIES
Series Title
Applied optimization, 65.
SUMMARY OR ABSTRACT
Text of Note
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.