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Springer Interior Point Techniques in Optimization - Springer Applied

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Description

Interior point methods have transformed operations research and mathematical programming, enabling efficient solutions to large-scale linear, nonlinear and combinatorial optimization problems in real-world applications. This comprehensive volume explores the theoretical foundations and practical algorithms underlying these powerful techniques, covering complementarity conditions, sensitivity analysis, complexity analysis and Newton's method applications. The book examines how interior point approaches influence all major areas of mathematical programming, from algorithmic design to theoretical analysis. Essential reading for researchers, practitioners and students seeking to understand modern optimization methods that handle complex industrial and scientific problems with robust convergence and computational efficiency.

Key Features

Interior Point Techniques in Optimization covers advanced algorithmic methods for solving large-scale linear and nonlinear programming problems efficiently.

Springer's Applied Optimization series volume 6 provides comprehensive coverage of complementarity conditions and sensitivity analysis in optimization.

The book analyses Newton's method and complexity theory within the framework of interior point approaches for mathematical programming.

Explores decomposition techniques and practical applications of interior point methods across various industrial and scientific domains.

Addresses theoretical foundations that have advanced operations research and influenced contemporary mathematical programming development.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
03 December 2010
Listed Since
06 July 2010

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