Nonlinear Programming

Author: Peter Zörnig
Publisher: Walter de Gruyter
ISBN: 3110315289
Size: 48.64 MB
Format: PDF, Mobi
View: 4350
Download Read Online

Nonlinear Programming from the Author: Peter Zörnig. This book is an introduction to nonlinear programming, written for students from the fields of applied mathematics, engineering, and economy. It deals with theoretical foundations as well as solution methods, beginning with the classical procedures and reaching up to “modern” methods. Several examples, exercises with detailed solutions and applications are provided, making the text adequate for individual studies.

Introduction To Nonlinear Optimization

Author: Amir Beck
Publisher: SIAM
ISBN: 1611973643
Size: 73.60 MB
Format: PDF
View: 7437
Download Read Online

Introduction To Nonlinear Optimization from the Author: Amir Beck. This book provides the foundations of the theory of nonlinear optimization as well as some related algorithms and presents a variety of applications from diverse areas of applied sciences. The author combines three pillars of optimization?theoretical and algorithmic foundation, familiarity with various applications, and the ability to apply the theory and algorithms on actual problems?and rigorously and gradually builds the connection between theory, algorithms, applications, and implementation. Readers will find more than 170 theoretical, algorithmic, and numerical exercises that deepen and enhance the reader's understanding of the topics. The author includes offers several subjects not typically found in optimization books?for example, optimality conditions in sparsity-constrained optimization, hidden convexity, and total least squares. The book also offers a large number of applications discussed theoretically and algorithmically, such as circle fitting, Chebyshev center, the Fermat?Weber problem, denoising, clustering, total least squares, and orthogonal regression and theoretical and algorithmic topics demonstrated by the MATLAB? toolbox CVX and a package of m-files that is posted on the book?s web site.

Introduction To Optimization

Author: Pablo Pedregal
Publisher: Springer Science & Business Media
ISBN: 0387403981
Size: 58.61 MB
Format: PDF
View: 808
Download Read Online

Introduction To Optimization from the Author: Pablo Pedregal. This undergraduate textbook introduces students of science and engineering to the fascinating field of optimization. It is a unique book that brings together the subfields of mathematical programming, variational calculus, and optimal control, thus giving students an overall view of all aspects of optimization in a single reference. As a primer on optimization, its main goal is to provide a succinct and accessible introduction to linear programming, nonlinear programming, numerical optimization algorithms, variational problems, dynamic programming, and optimal control. Prerequisites have been kept to a minimum, although a basic knowledge of calculus, linear algebra, and differential equations is assumed.

Introduction To The Theory Of Nonlinear Optimization

Author: Johannes Jahn
Publisher: Springer Science & Business Media
ISBN: 3662032716
Size: 23.27 MB
Format: PDF, Docs
View: 3213
Download Read Online

Introduction To The Theory Of Nonlinear Optimization from the Author: Johannes Jahn. This book serves as an introductory text to optimization theory in normed spaces and covers all areas of nonlinear optimization. It presents fundamentals with particular emphasis on the application to problems in the calculus of variations, approximation and optimal control theory. The reader is expected to have a basic knowledge of linear functional analysis.

An Introduction To Nonlinear Optimization Theory

Author: Marius Durea
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110427354
Size: 55.20 MB
Format: PDF, Kindle
View: 5638
Download Read Online

An Introduction To Nonlinear Optimization Theory from the Author: Marius Durea. This book presents the main ideas and techniques in the field of continuous smooth and nonsmooth optimization.

Linear And Nonlinear Programming

Author: David G. Luenberger
Publisher: Springer
ISBN: 3319188429
Size: 58.42 MB
Format: PDF, Docs
View: 5840
Download Read Online

Linear And Nonlinear Programming from the Author: David G. Luenberger. This new edition covers the central concepts of practical optimization techniques, with an emphasis on methods that are both state-of-the-art and popular. One major insight is the connection between the purely analytical character of an optimization problem and the behavior of algorithms used to solve a problem. This was a major theme of the first edition of this book and the fourth edition expands and further illustrates this relationship. As in the earlier editions, the material in this fourth edition is organized into three separate parts. Part I is a self-contained introduction to linear programming. The presentation in this part is fairly conventional, covering the main elements of the underlying theory of linear programming, many of the most effective numerical algorithms, and many of its important special applications. Part II, which is independent of Part I, covers the theory of unconstrained optimization, including both derivations of the appropriate optimality conditions and an introduction to basic algorithms. This part of the book explores the general properties of algorithms and defines various notions of convergence. Part III extends the concepts developed in the second part to constrained optimization problems. Except for a few isolated sections, this part is also independent of Part I. It is possible to go directly into Parts II and III omitting Part I, and, in fact, the book has been used in this way in many universities. New to this edition is a chapter devoted to Conic Linear Programming, a powerful generalization of Linear Programming. Indeed, many conic structures are possible and useful in a variety of applications. It must be recognized, however, that conic linear programming is an advanced topic, requiring special study. Another important topic is an accelerated steepest descent method that exhibits superior convergence properties, and for this reason, has become quite popular. The proof of the convergence property for both standard and accelerated steepest descent methods are presented in Chapter 8. As in previous editions, end-of-chapter exercises appear for all chapters. From the reviews of the Third Edition: “... this very well-written book is a classic textbook in Optimization. It should be present in the bookcase of each student, researcher, and specialist from the host of disciplines from which practical optimization applications are drawn.” (Jean-Jacques Strodiot, Zentralblatt MATH, Vol. 1207, 2011)

Linear And Nonlinear Optimization

Author: Igor Griva
Publisher: SIAM
ISBN: 0898717736
Size: 16.75 MB
Format: PDF, Mobi
View: 1520
Download Read Online

Linear And Nonlinear Optimization from the Author: Igor Griva. Provides an introduction to the applications, theory, and algorithms of linear and nonlinear optimization. The emphasis is on practical aspects - discussing modern algorithms, as well as the influence of theory on the interpretation of solutions or on the design of software. The book includes several examples of realistic optimization models that address important applications. The succinct style of this second edition is punctuated with numerous real-life examples and exercises, and the authors include accessible explanations of topics that are not often mentioned in textbooks, such as duality in nonlinear optimization, primal-dual methods for nonlinear optimization, filter methods, and applications such as support-vector machines. The book is designed to be flexible. It has a modular structure, and uses consistent notation and terminology throughout. It can be used in many different ways, in many different courses, and at many different levels of sophistication.