Practical Mathematical Optimization

An Introduction to Basic Optimization Theory and Classical and New Gradient-Based Algorithms
1. Auflage 2005. Corr. 2. printing 2005
ISBN: 978-0-387-29824-5
Verlag: Springer US

Buch, Englisch, 257 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 429 g

Reihe: Applied Optimization

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.

Zielgruppe

Students taking senior- to graduate-level semester courses in optimization, as offered in mathematics, engineering, computer science, and operations research departments; practising professionals in the workplace

Autoren/Hrsg.

Snyman, Jan

Fachgebiete

• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Algorithmen & Datenstrukturen
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Computeranwendungen in der Mathematik
• Mathematik | Informatik Mathematik Mathematische Analysis Reelle Analysis
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Optimierung
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Numerische Mathematik
• Mathematik | Informatik Mathematik Operations Research

Inhaltsverzeichnis

Line Search Descent Methods for Unconstrained Minimization.- Standard Methods for Constrained Optimization.- New Gradient-Based Trajectory and Approximation Methods.- Example Problems.- Some Theorems.