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The Mathematics of Nonlinear Programming
The Mathematics of Nonlinear Programming

The Mathematics of Nonlinear Programming (Undergraduate Texts in Mathematics) by Anthony L. Peressini, Francis E. Sullivan, J.J. Uhl

The Mathematics of Nonlinear Programming (Undergraduate Texts in Mathematics)



The Mathematics of Nonlinear Programming (Undergraduate Texts in Mathematics) epub




The Mathematics of Nonlinear Programming (Undergraduate Texts in Mathematics) Anthony L. Peressini, Francis E. Sullivan, J.J. Uhl ebook
Page: 285
Format: djvu
Publisher:
ISBN: 3540966145, 9783540966142


The mathematical theory of elliptic PDEs. Time-dependent PDEs The book concludes with a discussion of the methods for nonlinear problems, such as Newton's method, and addresses the importance of hands-on work to facilitate learning. Language: English Released: 1988. Audience: This book is primarily intended for use in linear and nonlinear optimization courses for advanced undergraduate and graduate students. An internationally renowned authority in mechanics and applied mathematics, Dr. GO The Mathematics of Nonlinear Programming (Undergraduate Texts in Mathematics) Author: Anthony L. Publisher: Society for Industrial and Applied Mathematics 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. Lin's initial research in fluid mechanics and hydrodynamics stability and turbulence greatly influenced the field of fluid flow. Each chapter concludes with a set of exercises, including theoretical and programming problems, that allows readers to test their understanding of the presented theories and techniques. The Mathematics of Nonlinear Programming (Undergraduate Texts in Mathematics). The book offers several research technologies not yet well known among practitioners of discrete optimization, minimizes prerequisites for learning these methods, and provides a transition from linear discrete optimization to nonlinear discrete optimization.

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