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Complexity Theory: Exploring the Limits of Efficient Algorithms [Hardcover]

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Item description for Complexity Theory: Exploring the Limits of Efficient Algorithms by R. Pruim Ingo Wegener...

Complexity theory is the theory of determining the necessary resources for the solution of algorithmic problems and, therefore, the limits of what is possible with the available resources. An understanding of these limits prevents the search for non-existing efficient algorithms. This textbook considers randomization as a key concept and emphasizes the interplay between theory and practice:

New branches of complexity theory continue to arise in response to new algorithmic concepts, and its results- such as the theory of NP-completeness- have influenced the development of all areas of computer science.

The topics selected have implications for concrete applications, and the significance of complexity theory for today's computer science is stressed throughout.

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Item Specifications...

Pages   308
Est. Packaging Dimensions:   Length: 9.29" Width: 6.38" Height: 0.94"
Weight:   1.28 lbs.
Binding  Hardcover
Publisher   Springer
ISBN  3540210458  
ISBN13  9783540210450  

Availability  128 units.
Availability accurate as of May 29, 2017 05:44.
Usually ships within one to two business days from La Vergne, TN.
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More About R. Pruim Ingo Wegener

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Product Categories

1Books > Foreign Language Books > German > All German Books
2Books > Foreign Language Books > German > Nonfiction
3Books > Subjects > Computers & Internet > Computer Science > Software Engineering > Information Systems
4Books > Subjects > Computers & Internet > General
5Books > Subjects > Computers & Internet > Hardware > Microprocessors & System Design > Computer Design
6Books > Subjects > Computers & Internet > Programming > Algorithms > General

Reviews - What do customers think about Complexity Theory: Exploring the Limits of Efficient Algorithms?

good graduate level text  Sep 5, 2005
Wegener's book seems best suited for a graduate level course in algorithms or complexity. This subject is one of the key conceptual underpinnings of computing. For those of you desirous of a deep understanding of the complexity of a problem or algorithm to solve a problem, then the text furnishes good explanations.

All the classic problems are here. Knapsack. Travelling salesperson. And various black box approaches. The key demarcation in the text is between a problem that is NP complete and one that can be solved in polynomial time. But a virtue of the book is that even with an NP complete problem, it may well be possible to derive approximate solutions that are polynomial complete.

It's certainly not a simple book. Some of the problems are very hard. But that leaves room for you to improve on the current methods of solving them.

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