: 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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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 related interests in statistical computing and optimal control.
Ariela Sofer received the B. She received the D. Her major areas of interest are nonlinear optimization, and optimization in biomedical applications. She has been a gria 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.
Igor Griva (Author of Linear and Nonlinear Optimization. Igor Griva, Stephen G. Nash, Ariela Sofer)
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 method; 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. Customer Reviews Average Review.
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Please check below for Buy Online, Pick up in Store. Overview 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 linwar 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.
Linear and Nonlinear Optimization, Second Edition
It can be used in many different ways, in many different courses, and at many different levels of sophistication. About the Author Igor Griva received a B. His research focuses on theory and methods of nonlinear optimization and their application to problems in science and engineering. Table of Contents Preface; Part I.