Numerical optimization

By: Nocedal, JorgeContributor(s): Stephen J.WrightMaterial type: TextTextSeries: Springer series in operations researchPublication details: New York : Springer, ©1999Description: xx, 636 pages : illustrationsISBN: 9780387227429; 0387227423 ; 9780387987934; 0387987932 Subject(s): Mathematical optimizationDDC classification: 519.3
Contents:
Fundamentals of unconstrained optimization -- Line search methods -- Trust-region methods -- Conjugate gradient methods -- Practical newton methods -- Calculating derivatives -- Quasi-newton methods -- Large-scale quasi-newton and partially separable optimization -- Nonlinear least-squares problems -- Nonlinear equations -- Theory of constrained optimization -- Linear programming: the simplex method -- Linear programming interior-point methods -- Fundamentals of algorithms for nonlinear constrained optimization -- Quadratic programming -- Penalty, barrier, and augmented largrangian methods -- Sequential quadratic programming.
Summary: "Numerical Optimization presents a comprehensive and up-to-date description of the most effective methods in continuous optimization. It responds to the growing interest in optimization in engineering, science, and business by focusing on the methods that are best suited to practical problems."--BOOK JACKET. "Because of the emphasis on practical methods, as well as the extensive illustrations and exercises, the book is accessible to a wide audience. It can be used as a graduate text in engineering, operations research, mathematics, computer science, and business. It also serves as a handbook for researchers and practitioners in the field."--Jacket
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Reference 519.3 NOC (Browse shelf(Opens below)) Available 009881
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Includes Index

Fundamentals of unconstrained optimization --
Line search methods --
Trust-region methods --
Conjugate gradient methods --
Practical newton methods --
Calculating derivatives --
Quasi-newton methods --
Large-scale quasi-newton and partially separable optimization --
Nonlinear least-squares problems --
Nonlinear equations --
Theory of constrained optimization --
Linear programming: the simplex method --
Linear programming interior-point methods --
Fundamentals of algorithms for nonlinear constrained optimization --
Quadratic programming --
Penalty, barrier, and augmented largrangian methods --
Sequential quadratic programming.

"Numerical Optimization presents a comprehensive and up-to-date description of the most effective methods in continuous optimization. It responds to the growing interest in optimization in engineering, science, and business by focusing on the methods that are best suited to practical problems."--BOOK JACKET. "Because of the emphasis on practical methods, as well as the extensive illustrations and exercises, the book is accessible to a wide audience. It can be used as a graduate text in engineering, operations research, mathematics, computer science, and business. It also serves as a handbook for researchers and practitioners in the field."--Jacket

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