| Numerical Optimization 2006 Edition Contributor(s): Nocedal, Jorge (Author), Wright, Stephen (Author) |
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ISBN: 0387303030 ISBN-13: 9780387303031 Publisher: Springer OUR PRICE: $75.99 Product Type: Hardcover - Other Formats Published: July 2006 Annotation: Numerical Optimization presents a comprehensive and up-to-date description of the most effective methods in continuous optimization. It responds to the growing interest in optimization in engineering, science, and business by focusing on the methods that are best suited to practical problems. For this new edition the book has been thoroughly updated throughout. There are new chapters on nonlinear interior methods and derivative-free methods for optimization, both of which are used widely in practice and the focus of much current research. Because of the emphasis on practical methods, as well as the extensive illustrations and exercises, the book is accessible to a wide audience. It can be used as a graduate text in engineering, operations research, mathematics, computer science, and business. It also serves as a handbook for researchers and practitioners in the field. The authors have strived to produce a text that is pleasant to read, informative, and rigorous - one that reveals both the beautiful nature of the discipline and its practical side. There is a selected solutions manual for instructors for the new edition. |
| Additional Information |
| BISAC Categories: - Mathematics | Linear & Nonlinear Programming - Mathematics | Applied - Business & Economics | Operations Research |
| Dewey: 519.6 |
| LCCN: 2006923897 |
| Series: Springer Series in Operations Research and Financial Engineering |
| Physical Information: 1.75" H x 7.28" W x 10.15" (3.06 lbs) 688 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: Optimization is an important tool used in decision science and for the analysis of physical systems used in engineering. One can trace its roots to the Calculus of Variations and the work of Euler and Lagrange. This natural and reasonable approach to mathematical programming covers numerical methods for finite-dimensional optimization problems. It begins with very simple ideas progressing through more complicated concepts, concentrating on methods for both unconstrained and constrained optimization. |