Overview
- Presents the theory in a straightforward readable manner
- This is the first compact reference to address difficulties that inhibit broad use of gradient-based methods
- Shows how to apply optimization theory and algorithms in such fields as engineering, physics, chemistry, or business economics
- Includes theorems of particular interest and many worked-out example problems
- Includes supplementary material: sn.pub/extras
Part of the book series: Applied Optimization (APOP, volume 97)
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Table of contents (6 chapters)
Keywords
About this book
Authors and Affiliations
Bibliographic Information
Book Title: Practical Mathematical Optimization
Book Subtitle: An Introduction to Basic Optimization Theory and Classical and New Gradient-Based Algorithms
Authors: Jan A. Snyman
Series Title: Applied Optimization
DOI: https://doi.org/10.1007/b105200
Publisher: Springer New York, NY
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer-Verlag US 2005
Softcover ISBN: 978-0-387-29824-5Published: 29 November 2005
eBook ISBN: 978-0-387-24349-8Published: 15 December 2005
Series ISSN: 1384-6485
Edition Number: 1
Number of Pages: XX, 258
Topics: Optimization, Algorithms, Operations Research, Management Science, Numerical Analysis