Practical Mathematical Optimization : An Introduction to Basic Optimization Theory and Classical and New Gradient-Based Algorithms

An Introduction to Basic Optimization Theory and Classical and New Gradient-Based Algorithms

By: Jan Snyman

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Paperback | 1 January 2006

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278 Pages

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It is intended that this book be used in senior- to graduate-level semester courses in optimization, as offered in mathematics, engineering, com- puter science and operations research departments. Hopefully this book will also be useful to practising professionals in the workplace. The contents of the book represent the fundamental optimization mate- rial collected and used by the author, over a period of more than twenty years, in teaching Practical Mathematical Optimization to undergradu- ate as well as graduate engineering and science students at the University of Pretoria. The principal motivation for writing this work has not been the teaching of mathematics per se, but to equip students with the nec- essary fundamental optimization theory and algorithms, so as to enable them to solve practical problems in their own particular principal fields of interest, be it physics, chemistry, engineering design or business eco- nomics. The particular approach adopted here follows from the author's own personal experiences in doing research in solid-state physics and in mechanical engineering design, where he was constantly confronted by problems that can most easily and directly be solved via the judicious use of mathematical optimization techniques. This book is, however, not a collection of case studies restricted to the above-mentioned specialized research areas, but is intended to convey the basic optimization princi- ples and algorithms to a general audience in such a way that, hopefully, the application to their own practical areas of interest will be relatively simple and straightforward.

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You Can Find This Book In

Non-Fiction Mathematics Optimisation Linear Programming Computing & I.T.Computer Programming & Software Development Algorithms & Data Structures Probability & Statistics Applied Mathematics Business & Management Operational Research

Preface Table of Notation
Introduction
Line Search Descent Methods for Unconstrained Minimization
Standard Methods for Constrained Optimization
New Gradient-Based Trajectory and Approximation Methods
Example Problems
Some Theorems
The Simplex Method for Linear Programming Problems
Bibliography
Index
Table of Contents provided by Publisher. All Rights Reserved.

Practical Mathematical Optimization : An Introduction to Basic Optimization Theory and Classical and New Gradient-Based Algorithms

An Introduction to Basic Optimization Theory and Classical and New Gradient-Based Algorithms

At a Glance

Paperback

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How to return your order

Defective items

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