Optimization Theory and Methods: Nonlinear Programming / Edition 1

Optimization Theory and Methods: Nonlinear Programming / Edition 1

ISBN-10:
0387249753
ISBN-13:
9780387249759
Pub. Date:
05/24/2006
Publisher:
Springer US
ISBN-10:
0387249753
ISBN-13:
9780387249759
Pub. Date:
05/24/2006
Publisher:
Springer US
Optimization Theory and Methods: Nonlinear Programming / Edition 1

Optimization Theory and Methods: Nonlinear Programming / Edition 1

$199.99
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Overview

This book, a result of the authors’ teaching and research experience in various universities and institutes over the past ten years, can be used as a textbook for an optimization course for graduates and senior undergraduates. It systematically describes optimization theory and several powerful methods, including recent results. For most methods, the authors discuss an idea’s motivation, study the derivation, establish the global and local convergence, describe algorithmic steps, and discuss the numerical performance. The book deals with both theory and algorithms of optimization concurrently. It also contains an extensive bibliography with 366 references. Finally, apart from its use for teaching, Optimization Theory and Methods is also very beneficial for doing research.

Audience

This book is intended for senior students, graduates, teachers, and researchers in optimization, operations research, computational mathematics, applied mathematics, and some engineering and economics. It will also be useful for scientists in engineering and economics.


Product Details

ISBN-13: 9780387249759
Publisher: Springer US
Publication date: 05/24/2006
Series: Springer Optimization and Its Applications , #1
Edition description: 2006
Pages: 687
Product dimensions: 6.14(w) x 9.25(h) x 0.06(d)

Table of Contents

Line Search.- Newton’s Methods.- Conjugate Gradient Method.- Quasi-Newton Methods.- Trust-Region Methods and Conic Model Methods.- Solving Nonlinear Least-Squares Problems.- Theory of Constrained Optimization.- Quadratic Programming.- Penalty Function Methods.- Feasible Direction Methods.- Sequential Quadratic Programming.- Trust-Region Methods for Constrained Problems.- Nonsmooth Optimization.
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