Nonlinear Optimization

Name: Nonlinear Optimization
Price: 34.56 USD
Availability: InStock
ISBN: 9780691119151

ISBN-10: 0691119155

ISBN-13: 9780691119151

Edition: 2006

Authors: Andrzej Ruszczynski

List price: $115.00

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Description:

Optimization is one of the most important areas of modern applied mathematics, with applications in fields from engineering and economics to finance, statistics, management science, and medicine. While many books have addressed its various aspects,Nonlinear Optimizationis the first comprehensive treatment that will allow graduate students and researchers to understand its modern ideas, principles, and methods within a reasonable time, but without sacrificing mathematical precision. Andrzej Ruszczynski, a leading expert in the optimization of nonlinear stochastic systems, integrates the theory and the methods of nonlinear optimization in a unified, clear, and mathematically rigorous fashion,…

Book details

List price: $115.00
Copyright year: 2006
Publisher: Princeton University Press
Publication date: 1/22/2006
Binding: Hardcover
Pages: 464
Size: 6.54" wide x 9.57" long x 1.38" tall
Weight: 1.936
Language: English



Preface



Introduction



Theory



Elements of Convex Analysis



Convex Sets



Cones



Extreme Points



Convex Functions



Subdifferential Calculus



Conjugate Duality



Optimality Conditions



Unconstrained Minima of Differentiable Functions



Unconstrained Minima of Convex Functions



Tangent Cones



Optimality Conditions for Smooth Problems



Optimality Conditions for Convex Problems



Optimality Conditions for Smooth-Convex Problems



Second Order Optimality Conditions



Sensitivity



Lagrangian Duality



The Dual Problem



Duality Relations



Conic Programming



Decomposition



Convex Relaxation of Nonconvex Problems



The Optimal Value Function



The Augmented Lagrangian



Methods



Unconstrained Optimization of Differentiable Functions



Introduction to Iterative Algorithms



Line Search



The Method of Steepest Descent



Newton's Method



The Conjugate Gradient Method



Quasi-Newton Methods



Trust Region Methods



Nongradient Methods



Constrained Optimization of Differentiable Functions



Feasible Point Methods



Penalty Methods



The Basic Dual Method



The Augmented Lagrangian Method



Newton's Method



Barrier Methods



Nondifferentiable Optimization



The Subgradient Method



The Cutting Plane Method



The Proximal Point Method



The Bundle Method



The Trust Region Method



Constrained Problems



Composite Optimization



Nonconvex Constraints[406



Stability of Set-Constrained Systems



Linear-Conic Systems



Set-Constrained Linear Systems



Set-Constrained Nonlinear Systems


Further Reading


Bibliography


Index