The aim of this book is to provide an appreciation of the R tools available for optimization problems. Most users of R are not specialists in computation and the workings of the specialized tools are a black box. This can lead to mis-application, therefore users need help in making appropriate choic
Smooth Nonlinear Optimization in R n
โ Scribed by Tamรกs Rapcsรกk (auth.)
- Publisher
- Springer US
- Year
- 1997
- Tongue
- English
- Leaves
- 381
- Series
- Nonconvex Optimization and Its Applications 19
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
Experience gained during a ten-year long involvement in modelling, programยญ ming and application in nonlinear optimization helped me to arrive at the conclusion that in the interest of having successful applications and efficient software production, knowing the structure of the problem to be solved is inยญ dispensable. This is the reason why I have chosen the field in question as the sphere of my research. Since in applications, mainly from among the nonconvex optimization models, the differentiable ones proved to be the most efficient in modelling, especially in solving them with computers, I started to deal with the structure of smooth optimization problems. The book, which is a result of more than a decade of research, can be equally useful for researchers and stuยญ dents showing interest in the domain, since the elementary notions necessary for understanding the book constitute a part of the university curriculum. I inยญ tended dealing with the key questions of optimization theory, which endeavour, obviously, cannot bear all the marks of completeness. What I consider the most crucial point is the uniform, differential geometric treatment of various questions, which provides the reader with opportunities for learning the structure in the wide range, within optimization problems. I am grateful to my family for affording me tranquil, productive circumstances. I express my gratitude to F.
โฆ Table of Contents
Front Matter....Pages i-xiii
Introduction....Pages 1-6
Nonlinear Optimization Problems....Pages 7-25
Optimality Conditions....Pages 27-36
Geometric Background of Optimality Conditions....Pages 37-44
Deduction of the Classical Optimality Conditions in Nonlinear Optimization....Pages 45-60
Geodesic Convex Functions....Pages 61-86
On the Connectedness of the Solution Set to Complementarity Systems....Pages 87-110
Nonlinear Coordinate Representations....Pages 111-139
Tensors in Optimization....Pages 141-166
Geodesic Convexity on R + n ....Pages 167-183
Variable Metric Methods Along Geodesics....Pages 185-206
Polynomial Variable Metric Methods For Linear Optimization....Pages 207-230
Special Function Classes....Pages 231-251
Fenchelโs Unsolved Problem of Level Sets....Pages 253-270
An Improvement of the Lagrange Multiplier Rule for Smooth Optimization Problems....Pages 271-284
Back Matter....Pages 285-375
โฆ Subjects
Optimization; Operation Research/Decision Theory; Differential Geometry; Convex and Discrete Geometry
๐ SIMILAR VOLUMES
A textbook for a one-semester beginning graduate course for students of engineering, economics, operations research, and mathematics. Students are expected to have a good grounding in basic real analysis and linear algebra.