Buch, Englisch, Band 97, 257 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 429 g
Reihe: Applied Optimization
An Introduction to Basic Optimization Theory and Classical and New Gradient-Based Algorithms
Buch, Englisch, Band 97, 257 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 429 g
Reihe: Applied Optimization
ISBN: 978-0-387-29824-5
Verlag: Springer US
This book presents basic optimization principles and gradient-based algorithms to a general audience in a brief and easy-to-read form, without neglecting rigor. The text is structured to let professionals apply optimization theory and algorithms to their own practical fields of interest, such as engineering, physics, chemistry, or business economics. Most importantly, due attention is paid to the difficulties - such as noise, discontinuities, expense of function evaluations, and the existence of multiple minima - that often unnecessarily inhibit the use of gradient-based methods. In a separate chapter on new gradient-based methods developed by the author and his coworkers, it is shown how these difficulties may be overcome without losing the desirable features of classical gradient-based methods. The text includes theorems of special interest, and many worked examples.
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.
Fachgebiete
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Numerische Mathematik
- Mathematik | Informatik Mathematik Mathematische Analysis Reelle Analysis
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Computeranwendungen in der Mathematik
- Mathematik | Informatik Mathematik Operations Research
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Optimierung
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Algorithmen & Datenstrukturen
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
Weitere Infos & Material
Line Search Descent Methods for Unconstrained Minimization.- Standard Methods for Constrained Optimization.- New Gradient-Based Trajectory and Approximation Methods.- Example Problems.- Some Theorems.
