Linear and nonlinear optimization
By: Igor Griva, Stephen G. Nash, Ariela Sofer.
Contributors: Nash, Stephen; Sofer, Ariela.
Edition: 2nd ed.
Publisher: Society for Industrial and Applied Mathematics
Published: 2008
Place of publication: Philadelphia
Language: eng
Number of pages: 742
ISBN-13: 9780898716610
Subjects: Linear programming; Nonlinear programming
Description: "This book introduces the applications, theory, and algorithms of linear and nonlinear optimization, with an emphasis on the practical aspects of the material. Its unique modular structure provides flexibility to accommodate the varying needs of instructors, students, and practitioners with different levels of sophistication in these topics. 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.

Linear and Nonlinear Optimization, Second Edition is primarily intended for use in linear and nonlinear optimization courses for advanced undergraduate and graduate students. It is also appropriate as a tutorial for researchers and practitioners who need to understand the modern algorithms of linear and nonlinear optimization to apply them to problems in science and engineering."--Jacket.
Notes: Includes bibliographical references and index.
Table of contents: title: Optimization models; title: Fundamentals of optimization; title: Representation of linear constraints; title: Geometry of linear programming; title: The simplex method; title: Duality and sensitivity; title: Enhancements of the simplex method; title: Network problems; title: Computational complexity of linear programming; title: Interior-point methods of linear programming; title: Basics of unconstrained optimization; title: Methods for unconstrained optimization; title: Low-storage methods for unconstrained problems; title: Optimality conditions for constrained problems; title: Feasible-point methods; title: Penalty and barrier methods.