| Linear and Nonlinear Programming: Second Edition Contributor(s): Luenberger, David G. (Author) |
|
 |
ISBN: 1402075936 ISBN-13: 9781402075933 Publisher: Springer OUR PRICE: $123.49 Product Type: Hardcover Published: September 2003 Annotation: "Linear and Nonlinear Programming" is considered a classic textbook in Optimization. While it is a classic, it also reflects modern theoretical insights. These insights provide structure to what might otherwise be simply a collection of techniques and results, and this is valuable both as a means for learning existing material and for developing new results. One major insight of this type is the connection between the purely analytical character of an optimization problem, expressed perhaps by properties of the necessary conditions, and the behavior of algorithms used to solve a problem. This was a major theme of the first edition of this book and the second edition expands and further illustrates this relationship. "Linear and Nonlinear Programming" covers the central concepts of practical optimization techniques. It is designed for either self-study by professionals or classroom work at the undergraduate or graduate level for technical students. Like the field of optimization itself, which involves many classical disciplines, the book should be useful to system analysts, operations researchers, numerical analysts, management scientists, and other specialists from the host of disciplines from which practical optimization applications are drawn. |
| Additional Information |
| BISAC Categories: - Computers | Programming Languages - General - Mathematics | Linear & Nonlinear Programming - Science | Mechanics - Dynamics |
| Dewey: 519.7 |
| LCCN: 2004296891 |
| Physical Information: 1.2" H x 6.26" W x 9.78" (1.89 lbs) 492 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: The original edition of this book was celebrated for its coverage of the central concepts of practical optimization techniques. This updated edition expands and illuminates the connection between the purely analytical character of an optimization problem, expressed by properties of the necessary conditions, and the behavior of algorithms used to solve a problem. Incorporating modern theoretical insights, this classic text is even more useful. |
