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Foreword, George B. Dantzig
Preface Acknowledgments Glossary of Symbols
1. Introduction
PART I. THEORY
2. Generalized Distances and Generalized Projections
3. Proximal Minimization with D-Functions
4. Penalty Methods, Barrier Methods and Augmented Lagrangians
PART II. ALGORITHMS
5. Iterative Methods for Convex Feasibility Problems
6. Iterative Algorithms for Linearly Constrained Optimization Problems
7. Model Decomposition Algorithms
8. Decompositions in Interior Point Algorithms
PART III. APPLICATIONS
9. Matrix Estimation Problems
10. Image Reconstruction from Projections
11. The Inverse Problem in Radiation Therapy Treatment Planning
12. Multicommodity Network Flow Problems
13. Planning Under Uncertainty
14. Decompositions for Parallel Computing
15. Numerical Investigations
| Price | Condition | Delivery | Seller | Action |
| $217.30 | Digital |
| WonderClub |
Michael Dewees
reviewed Parallel Optimization: Theory, Algorithms, and Applications on January 23, 2014
Parallel Optimization
A good book in content and diverse information, but the author needs to explain processes better, many topics needed more details to flesh-out his message.
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Add Parallel Optimization: Theory, Algorithms, and Applications, This book offers a unique pathway to methods of parallel optimization by introducing parallel computing ideas into both optimization theory and into some numerical algorithms for large-scale optimization problems. The three parts of the book bring togethe, Parallel Optimization: Theory, Algorithms, and Applications to the inventory that you are selling on WonderClubX
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Add Parallel Optimization: Theory, Algorithms, and Applications, This book offers a unique pathway to methods of parallel optimization by introducing parallel computing ideas into both optimization theory and into some numerical algorithms for large-scale optimization problems. The three parts of the book bring togethe, Parallel Optimization: Theory, Algorithms, and Applications to your collection on WonderClub |