The new edition of this book presents a comprehensive and up-to-date description of the most effective methods in continuous optimization. Its publication responds to the growing interest in optimization in engineering, science, and business by focusing on the methods that are best suited to practical problems. This new edition has been thoroughly updated throughout. There are new chapters on nonlinear interior methods and derivative-free methods for optimization, both of which are widely used in practice and are the focus of much current research. Because of the emphasis on practical methods, as well as the extensive illustrations and exercises, the book is accessible to a wide audience including graduate students, researchers and practitioners. The authors have produced a text that is pleasant to read, informative and rigorous. It reveals both the beautiful nature of the discipline and its practical side.
Rezensionen / Stimmen
MMOR Mathematical Methods of Operations Research, 2001: "The books looks very suitable to be used in an graduate-level course in optimization for students in mathematics, operations research, engineering, and others. Moreover, it seems to be very helpful to do some self-studies in optimization, to complete own knowledge and can be a source of new ideas... I recommend this excellent book to everyone who is interested in optimization problems."
Reihe
Auflage
Sprache
Verlagsort
Zielgruppe
Für höhere Schule und Studium
Research
Editions-Typ
Illustrationen
Maße
Höhe: 260 mm
Breite: 184 mm
Dicke: 44 mm
Gewicht
ISBN-13
978-0-387-30303-1 (9780387303031)
DOI
10.1007/978-0-387-40065-5
Schweitzer Klassifikation
Fundamentals of Unconstrained Optimization.- Line Search Methods.- Trust-Region Methods.- Conjugate Gradient Methods.- Quasi-Newton Methods.- Large-Scale Unconstrained Optimization.- Calculating Derivatives.- Derivative-Free Optimization.- 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 and Augmented Lagrangian Methods.- Sequential Quadratic Programming.- Interior-Point Methods for Nonlinear Programming.