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Computers and Intractability: A Guide to the Theory of NP-Completeness (Series of Books in the Mathematical Sciences) 1St Edition Edition

4.7 out of 5 stars 19 customer reviews
ISBN-13: 978-0716710455
ISBN-10: 0716710455
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Editorial Reviews

Amazon.com Review

This book's introduction features a humorous story of a man with a line of people behind him, who explains to his boss, "I can't find an efficient algorithm, but neither can all these famous people." This man illustrates an important quality of a class of problems, namely, the NP-complete problems: if you can prove that a problem is in this class, then it has no known polynomial-time solution that is guaranteed to work in general. This quality implies that the problem is difficult to deal with in practice.

The focus of this book is to teach the reader how to identify, deal with, and understand the essence of NP-complete problems; Computers and Intractability does all of those things effectively. In a readable yet mathematically rigorous manner, the book covers topics such as how to prove that a given problem is NP-complete and how to cope with NP-complete problems. (There is even a chapter on advanced topics, with numerous references.) Computers and Intractability also contains a list of more than 300 problems--most of which are known to be NP-complete--with comments and references.

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Product Details

  • Series: Series of Books in the Mathematical Sciences
  • Paperback: 340 pages
  • Publisher: W. H. Freeman; 1St Edition edition (January 15, 1979)
  • Language: English
  • ISBN-10: 0716710455
  • ISBN-13: 978-0716710455
  • Product Dimensions: 6.1 x 0.7 x 9.2 inches
  • Shipping Weight: 1.1 pounds (View shipping rates and policies)
  • Average Customer Review: 4.7 out of 5 stars  See all reviews (19 customer reviews)
  • Amazon Best Sellers Rank: #330,799 in Books (See Top 100 in Books)

Customer Reviews

Top Customer Reviews

Format: Paperback
All those who deals with Computer Science,
Mathematics and Engineering have to face the
reality that certain problems seem really hard
to solve. Even with the more sophisticated, and
technologically advanced among the currently
available computers---and among those that are to
come in the next several years---, it seems highly
likely that we cannot efficiently solve certain
specific problems.

A first well written and systematic account on
the hardness of this problems is the 1979 book on
the theory of NP completeness by Michael R. Garey
and David S. Johnson: Computers and
Intractability, A Guide to the Theory of
NP-Completeness (W.H. Freeman and Company, San
Francisco). It is amazing how, after all these
years, this book remains a fundamental one to be
introduced on what can be effectively and
efficiently solved by computers and above all on
what it seems not efficiently solvable,
independently of the advances of technology.
Other texts have been published after that one,
as for example the recent clear and complete
overview on what has been done and extensively
researched since then that has been given by
Christos H. Papadimitriou in his book
Computational Complexity (Addison-Wesley, 1994).
Nevertheless, the Garey-Johnson book---as it is
often familiarly called---remains the fundamental
book for a clear introduction to this central
problem of what is tractable by computers.
Read more ›
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Format: Paperback
Every graduate CS student will probably encounter this book--it is a classic.
But long after that course in NP theory was over, the astonishment of a different aspect of the book remains.
One course assignment was the development of 15 polynomial reduction proofs (proving the computational complexity equivalence of pairs of NP problems). Part of these proofs can be simple geometric shapes, locations and connecting lines, which are defined as elements in the 2 problems. Because the elements are rigorously defined, the resulting geometric pictures model rigorous proofs of equivalence.
I was astounded at the power of such abstractions (which most programmers perhaps wouldn't even recognize as legitimate proofs). This experience underlined the fact that rigorous logical proof may take many outer forms, whether mathematical equations, formal symbolic logic proofs such as the Irving Copi notation, or simple geometric drawings.
Many veins of rich ore may be mined from this work, and only 1 of them is NP theory. But the reader must be ready to do battle with some difficult ideas, and mathematical notation which can obscure the creativity of the material covered. (For astounding creativity, examine Cooke's Theorem proving that the Satisfiability problem is NP-Complete!)
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Format: Paperback
I first read this book while researching heuristic techniques for reaching "good enough" solutions to the Travelling Salesman problem. "Computers and Intractability" was a breath of fresh air. It was as rigorous as any mathematical treatise, but written in a way that even a non-math major could understand. If you ever want to know why computers are so buggy, you'll know the mathematical reason for this within the first few pages of this book. By the time you reach the end, you'll never trust cryptography to absolutely, without a doubt, keep data secure for long, if at all.
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Format: Paperback Verified Purchase
I have to say that this is a true classic. It gives a very nice treatment of what is NP-completeness in a fashion that really defends the topic well. It gives nice illustrations to show different situations and how to deal with it. But after the first couple of chapters it does get a little out there with the proofs it does. It is still approachable, but it assumes that the reader is already familiar with the basics of combinatorial complexity, especially in reductions. I would only recommend this book to readers who has gone through such books as Introduction to Algorithms by Cormen et al. or Combinatorial Complexity by Papadimitriou and Steiglitz. Those two books are more for beginners and this book should be one to help anyone interested in NP-complete problems to get more practice and depth understanding. Overall a great book for anyone interested in the topic. The grand challenge is to reduce everything to at least something within the 150 problems listed on your own.
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By Todd Ebert on September 14, 2000
Format: Paperback
I think every computer science student should read some of this book to learn about complexity theory and the notions reducibilty and completeness. Moreover, you may come across a problem that you have to show is NP or P complete, and the examples in the book provide a good model for doing so. Papadimitriou's book on complexity is also a great place to learn more about the subject.
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By A Customer on December 2, 2001
Format: Paperback
Yes, it's a classic. Yes, every computer scientist MUST own it. But enormous significant progress has been made in the field of NP-completeness (and computational complexity more generally) in the two decades since this book was published. An up-to-date edition -- which would probably be well over a thousand pages long -- has been badly needed for years.
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