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Produktbild: Practical Optimization
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Practical Optimization Algorithms and Engineering Applications

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Beschreibung

This textbook provides a hands-on treatment of the subject of optimization. A comprehensive set of problems and exercises makes it suitable for use in one or two semesters of an advanced undergraduate course or a first-year graduate course. Each half of the book contains a full semester’s worth of complementary...

Beschreibung

This textbook provides a hands-on treatment of the subject of optimization. A comprehensive set of problems and exercises makes it suitable for use in one or two semesters of an advanced undergraduate course or a first-year graduate course. Each half of the book contains a full semester’s worth of complementary yet stand-alone material. The practical orientation of the topics chosen and a wealth of useful examples also make the book suitable as a reference work for practitioners in the field.

In this second edition the authors have added sections on recent innovations, techniques, and methodologies.

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

20.10.2021

Abbildungen

XXIV, 722 p. 154 illus.

Verlag Springer Us

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

20.10.2021

Abbildungen

XXIV, 722 p. 154 illus.

Verlag Springer Us
Seitenzahl

722

Maße (L/B/H)

24,1/16/4,6 cm

Gewicht

1222 g

Farbe

Silbergrau / Aubergine

Auflage

Second Edition 2021

Sprache

Englisch

ISBN

978-1-07-160841-8

Herstelleradresse

Springer-Verlag GmbH
Europaplatz 3
69115 Heidelberg
DE

Email: ProductSafety@springernature.com

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  • Produktbild: Practical Optimization
  • The Optimization Problem.- Basic Principles.- General Properties of Algorithms.- One-Dimensional Optimization.- Basic Multidimensional Gradient Methods.- Conjugate-Direction Methods.- Quasi-Newton Methods.- Minimax Methods.- Applications of Unconstrained Optimization.- Fundamentals of Constrained Optimization.- Linear Programming Part I: The Simplex Method.- Linear Programming Part II: Interior-Point Methods.- Quadratic and Convex Programming.- Semidefinite and Second-Order Cone Programming.- General Nonlinear Optimization Problems.- Applications of Constrained Optimization.