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OverviewNumerical 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. For this new edition the book has been thoroughly updated throughout. There are new chapters on nonlinear interior methods and derivative-free methods for optimization, both of which are used widely in practice and 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. 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. The authors have strived to produce a text that is pleasant to read, informative, and rigorous - one that reveals both the beautiful nature of the discipline and its practical side. There is a selected solutions manual for instructors for the new edition. Full Product DetailsAuthor: Jorge Nocedal , Stephen WrightPublisher: Springer-Verlag New York Inc. Imprint: Springer-Verlag New York Inc. Edition: 2nd ed. 2006 Dimensions: Width: 17.80cm , Height: 3.60cm , Length: 23.50cm Weight: 3.340kg ISBN: 9780387303031ISBN 10: 0387303030 Pages: 664 Publication Date: 27 July 2006 Audience: College/higher education , Undergraduate , Postgraduate, Research & Scholarly Format: Hardback Publisher's Status: Active Availability: Awaiting stock ![]() The supplier is currently out of stock of this item. It will be ordered for you and placed on backorder. Once it does come back in stock, we will ship it out for you. Table of ContentsFundamentals 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.Reviews<p>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. <br> Author InformationTab Content 6Author Website:Countries AvailableAll regions |