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Home > Catalog > Paradigms for Fast Parallel Approximability
Paradigms for Fast Parallel Approximability


  • 32 b/w illus.
  • Page extent: 168 pages
  • Size: 244 x 170 mm
  • Weight: 0.28 kg
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 (ISBN-13: 9780521117920)

Manufactured on demand: supplied direct from the printer

$49.99 (C)

This book is a survey of the basic techniques for approximating combinatorial problems using parallel algorithms. Its core is a collection of techniques that can be used to provide parallel approximations for a wide range of problems, such as flows, coverings, matchings, traveling salesman problems, and graphs. For added clarity, the authors provide an introductory chapter containing the basic definitions and results. A final chapter deals with problems that cannot be approximated, and the book is rounded off by an appendix that gives a convenient summary of the problems described in the book. This book is an up-to-date reference for research workers in the area of algorithms and for graduate courses in the subject.


1. Introduction; 2. Basic concepts; 3. Extremal graph properties; 4. Rounding, interval partitioning and separation; 5. Primal-dual method; 6. Graph decomposition; 7. Further parallel approximations; 8. Non-approximability; 9. Syntactical defined phrases; Appendix: Definition of problems; Bibliography; Index.


"This monograph reads as smoothly as a single-author work. It can serve as an excellent reference for those interested in algorithmic and computational complexity results in parallel approximability. It can also serve as an excellent introduction to the field for theoretical researchers." Computing Reviews

"This is an excellent monograph that surveys one of the key parts of recent algorithm and complexity theory. This book really corresponds to its title Paradigms of fast parallel approximability. Because of this it is much more than a survey on the recent development in this area. I strongly recommend it as a valuable source for graduate courses in the subject also." Juraj Hromkovi^Dvc, Mathematical Reviews

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