Optimization : theory and practice
Optimization is an important field in its own right but also plays a central role in numerous applied sciences, including operations research, management science, economics, finance, and engineering. Optimization Theory and Practice offers a modern and well-balanced presentation of various optimizat...
Guardat en:
| Autors principals: | , |
|---|---|
| Format: | Livre numérique |
| Idioma: | Anglais |
| Publicat: |
New York, NY :
Springer New York
[20..].
Cham : Springer Nature |
| Edició: | 1st ed. 2010. |
| Col·lecció: | Springer Undergraduate Texts in Mathematics and Technology
|
| Accés en línia: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Nota: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Optimization, theory and practice, Wilhelm Forst, Dieter Hoffmann, New York, Springer, 2010, 1 vol. (XVIII-402 p.), Springer undergraduate texts in mathematics and technology, 978-0-387-78976-7 • Optimization, theory and practice, Wilhelm Forst, Dieter Hoffmann, New York, Springer, 2010, 1 vol. (XVIII-402 p.), Springer undergraduate texts in mathematics and technology, 978-0-387-78976-7 • Function spaces and potential theory, David R. Adams, Lars Inge Hedberg, 1996, Berlin, Springer, 1 vol. (XI-366 p.), Grundlehren der mathematischen Wissenschaften, 978-3-540-5706-08 • Optimization-Theory and Practice, Texte imprimé, 9781493939336 |
Taula de continguts:
- 1. Introduction: Examples of Optimization Problems, Historical Overview 2. Optimality Conditions: Convex Sets, Inequalities, Local First- and Second-Order Optimality Conditions, Duality 3. Unconstrained Optimization Problems: Elementary Search and Localization Methods, Descent Methods with Line Search, Trust Region Methods, Conjugate Gradient Methods, Quasi-Newton Methods 4. Linearly Constrained Optimization Problems: Linear and Quadratic Optimization, Projection Methods 5. Nonlinearly Constrained Optimization Methods: Penalty Methods, SQP Methods 6. Interior-Point Methods for Linear Optimization: The Central Path, Newton's Method for the Primal-Dual System, Path-Following Algorithms, Predictor-Corrector Methods 7. Semidefinite Optimization: Selected Special Cases, The S-Procedure, The Function logůet, Path-Following Methods, How to Solve SDO Problems?, Icing on the Cake: Pattern Separation via Ellipsoids 8. Global Optimization: Branch and Bound Methods, Cutting Plane Methods Appendices: A Second Look at the Constraint Qualifications, The Fritz John Condition, Optimization Software Tools for Teaching and Learning Bibliography Index of Symbols Subject Index