£119.87

Springer - Aspects of Semidefinite Programming (Applied Optimization)

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Description

Explore the advanced mathematical landscape of semidefinite programming with this specialized monograph from Springer. Often described as the next evolution of linear programming, semidefinite programming offers significant potential for researchers and practitioners in control theory, combinatorial optimization, and other mathematical fields. This text provides a deep dive into the fundamental theory of interior point algorithms. You will find detailed explanations regarding the properties of the central path and a thorough analysis of the most important algorithm classes. By extending successful interior point methods from linear programming to the semidefinite realm, this book serves as a vital resource for understanding these complex mathematical structures. Whether you are studying mathematical programming or looking for specific applications in optimization, this volume provides the necessary theoretical framework and analysis required to master these modern computational methods. It is a key addition to the Applied Optimization series for those focused on high-level algorithmic development.

Key Features

Covers the basic theory of interior point algorithms for semidefinite programming.

Includes the latest research results on the properties of the central path.

Provides detailed analysis of the most important classes of algorithms.

Explores applications in control theory and combinatorial optimization.

Extends successful linear programming interior point methods to semidefinite programming.

Part of the Applied Optimization series (Volume 65) from Springer.

Product Specifications

Format
Hardcover
Domain
Amazon UK
Release Date
31 March 2002
Listed Since
22 December 2006

Barcode

No barcode data available

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