: Linear and Nonlinear Optimization () by Igor Griva; Stephen G. Nash; Ariela Sofer and a great selection of similar New, Used. Provides an introduction to the applications, theory, and algorithms of linear and nonlinear optimization. The emphasis is on practical aspects. by Igor Griva, Stephen G. Nash, Ariela Sofer This book is primarily intended for use in linear and nonlinear optimization courses for advanced undergraduate.

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Linear and Nonlinear Optimization

Home Contact Us Help Free delivery worldwide. Linear and Nonlinear Optimization. Description Provides an introduction to the applications, theory, and algorithms of ilnear 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.

The Best Books of Check out the top books of the year on our page Best Books of Looking for beautiful books? Visit our Beautiful Books page and find lovely books for kids, photography lovers and more. Table of contents Preface; Part I. Fundamentals of optimization; 3.

Representation of linear constraints; Part II. Geometry of linear programming; 5.

The simplex method; 6. Duality and sensitivity; 7. Enhancements of the simplex nohlinear 8. Computational complexity of linear programming; Interior-point methods of linear programming; Part III. Basics of unconstrained optimization; Methods for unconstrained optimization; Low-storage methods for unconstrained problems; Part IV.

Optimality conditions for constrained problems; Penalty and barrier methods; Part V. Topics from linear algebra; Appendix B. Other fundamentals; Appendix C.

Linear and Nonlinear Optimization : Igor Griva :

His research focuses on theory and methods of nonlinear optimization and their application to problems in science and engineering. Stephen Nash received a B. Honors degree in mathematics in from the University of Alberta, Canada; and a Ph. His research activities are centered in scientific computing, especially nonlinear optimization, along with optumization interests in statistical computing and optimal control.


Ariela Sofer received the B. She received the D.

Linear and Nonlinear Optimization, Second Edition

Her major areas of interest are nonlinear ilnear, and optimization in biomedical applications. She has been a member of the editorial boards of the journals Operations Research and Management Science, and is coeditor on a subseries of the Annals of Operations Research on Operations Research in Medicine. Book ratings by Goodreads. Goodreads is the world’s largest site for readers optimiaztion over 50 million reviews.

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