| Titre : |
Numerical optimization |
| Type de document : |
texte imprimé |
| Auteurs : |
Jorge Nocedal, Auteur ; Stephen J.Wright, Auteur ; Stephen J.Wright |
| Editeur : |
Berlin ; London ; Cham : Springer |
| Année de publication : |
1999 |
| Importance : |
XX-636 p. |
| Présentation : |
ill. |
| Format : |
24 cm. |
| ISBN/ISSN/EAN : |
978-0-387-98793-4 |
| Note générale : |
Bibliogr. p.[611]-623. Index |
| Langues : |
Anglais (eng) |
| Mots-clés : |
Mathématique
Optimization |
| Index. décimale : |
519.863 Modèles d'optimisation |
| Résumé : |
"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. Drawing on their experiences in teaching, research, and consulting, the authors have produced a textbook that will be of interest to students and practitioners alike. Each chapter begins with the basics concepts and builds up gradually to the best techniques currently available. 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. Above all, 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. |
| Note de contenu : |
Summary:
1. Fundamentals of unconstrained optimization
2. Line search methods
3. Trust-region methods
4. Conjugate gradient methods
5. Practical Newton methods
6. Calculating derivates
7. Quasi-Newton methods
8. Large-scale Quasi-Newton and partially separable optimization
9. Nonlinear least-squares problems
10. Nonlinear equations
11. Theory of constrained optimization
12. Linear programming : the simplex method
13. Linear programming : interior-point methods
14. Fundamentals of algorithms for nonlinear constrained optimization
15. Quadratic programming
16. Penalty, Barrier, and augmented lagrangian methods
17. Sequential quadratic programming. |
Numerical optimization [texte imprimé] / Jorge Nocedal, Auteur ; Stephen J.Wright, Auteur ; Stephen J.Wright . - Berlin ; London ; Cham : Springer, 1999 . - XX-636 p. : ill. ; 24 cm. ISBN : 978-0-387-98793-4 Bibliogr. p.[611]-623. Index Langues : Anglais ( eng)
| Mots-clés : |
Mathématique
Optimization |
| Index. décimale : |
519.863 Modèles d'optimisation |
| Résumé : |
"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. Drawing on their experiences in teaching, research, and consulting, the authors have produced a textbook that will be of interest to students and practitioners alike. Each chapter begins with the basics concepts and builds up gradually to the best techniques currently available. 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. Above all, 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. |
| Note de contenu : |
Summary:
1. Fundamentals of unconstrained optimization
2. Line search methods
3. Trust-region methods
4. Conjugate gradient methods
5. Practical Newton methods
6. Calculating derivates
7. Quasi-Newton methods
8. Large-scale Quasi-Newton and partially separable optimization
9. Nonlinear least-squares problems
10. Nonlinear equations
11. Theory of constrained optimization
12. Linear programming : the simplex method
13. Linear programming : interior-point methods
14. Fundamentals of algorithms for nonlinear constrained optimization
15. Quadratic programming
16. Penalty, Barrier, and augmented lagrangian methods
17. Sequential quadratic programming. |
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