Parallel Optimization
Theory, Algorithms and Applications
Published on 12. March 1998
Book
Hardback
576 pages
978-0-19-510062-4 (ISBN)
Description
This book offers a unique pathway to methods of parallel optimization by introducing parallel computing ideas and techniques into both optimization theory, and into some numerical algorithms for large-scale optimization problems. The presentation is based on the recent understanding that rigorous mathematical analysis of algorithms, parallel computing techniques, and "hands-on" experimental work on real-world problems must go hand in hand in order to achieve the greatest advantage from novel parallel computing architectures. The three parts of the book thus bring together relevant theory, careful study of algorithms, and modelling of significant real world problems. The problem domains include: image reconstruction, radiation therapy treatment planning, transportation problems, portfolilo management, and matrix estimation. This text can be used both as a reference for researchers and as a text for advanced graduate courses.
Reviews / Votes
"This book presents a domain that arises where two different branches of science, namely parallel computations and the theory of constrained optimization, intersect with real life problems. This domain, called parallel optimization, has been developing rapidly under the stimulus of progress in computer technology. The book focuses on parallel optimization methods for large-scale constrained optimization problems and structured linear problems. . . . [It] coversa vast portion of parallel optimization, though full coverage of this domain, as the authors admit, goes far beyond the capacity of a single monograph. This book, however, in over 500 pages brings an
excellent and in-depth presentation of all the major aspects of a process which matches theory and methods of optimization with modern computers. The volume can be recommended for graduate students, faculty, and researchers in any of those fields."--Mathematical Reviews
"This book presents a domain that arises where two different branches of science, namely parallel computations and the theory of constrained optimization, intersect with real life problems. This domain, called parallel optimization, has been developing rapidly under the stimulus of progress in computer technology. The book focuses on parallel optimization methods for large-scale constrained optimization problems and structured linear problems. . . . [It] covers
a vast portion of parallel optimization, though full coverage of this domain, as the authors admit, goes far beyond the capacity of a single monograph. This book, however, in over 500 pages brings an
excellent and in-depth presentation of all the major aspects of a process which matches theory and methods of optimization with modern computers. The volume can be recommended for graduate students, faculty, and researchers in any of those fields."--Mathematical Reviews
More details
Series
Language
English
Place of publication
New York
United States
Target group
Professional and scholarly
Illustrations
halftones, line figures, tables
Dimensions
Height: 240 mm
Width: 161 mm
Thickness: 35 mm
Weight
1010 gr
ISBN-13
978-0-19-510062-4 (9780195100624)
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Schweitzer Classification
Persons
Content
Foreword ; Preface ; Glossary of Symbols ; 1. Introduction ; Part I Theory ; 2. Generalized Distances and Generalized Projections ; 3. Proximal Minimization with D-Functions ; Part II Algorithms ; 4. Penalty Methods, Barrier Methods and Augmented Lagrangians ; 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 Reconsturction 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