Numerical optimization : theoretical and practical aspects
Just as in its 1st edition, this book starts with illustrations of the ubiquitous character of optimization, and describes numerical algorithms in a tutorial way. It covers fundamental algorithms as well as more specialized and advanced topics for unconstrained and constrained problems. Most of the...
সংরক্ষণ করুন:
| প্রধান লেখক: | , , , |
|---|---|
| বিন্যাস: | Livre numérique |
| ভাষা: | Anglais |
| প্রকাশিত: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| সংস্করন: | 2nd ed. |
| মালা: | Universitext
|
| বিষয়গুলি: | |
| অনলাইন ব্যবহার করুন: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| টীকা: |
Description d'après consultation du 14 avril 2011 Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Numerical optimization, theoretical and practical aspects, J. Frederic Bonnans, J. Charles Gilbert, Claude Lemaréchal... [et autres], 2nd edition, 2006, Berlin, Springer, 1 volume (xiv-490 pages), Universitext, 978-3-540-35445-1 |
সূচিপত্রের সারণি:
- Unconstrained Problems General Introduction Basic Methods Line-Searches Newtonian Methods Conjugate Gradient Special Methods A Case Study: Seismic Reection Tomography Nonsmooth Optimization to Nonsmooth Optimization Some Methods in Nonsmooth Optimization Bundle Methods. The Quest for Descent Applications of Nonsmooth Optimization Computational Exercises Newton's Methods in Constrained Optimization Background Local Methods for Problems with Equality Constraints Local Methods for Problems with Equality and InequalityConstraints Exact Penalization Globalization by Line-Search Quasi-Newton Versions Interior-Point Algorithms for Linear and QuadraticOptimization Linearly Constrained Optimization and SimplexAlgorithm Linear Monotone Complementarity and Associated Vector Fields Predictor-Corrector Algorithms Non-Feasible Algorithms Self-Duality One-Step Methods Complexity of Linear Optimization Problems with Integer Data Karmarkar's Algorithm