Algorithmics for Hard Problems : Introduction to Combinatorial Optimization, Randomization, Approximation, and Heuristics
Second Edition 2004
Book Details
Format
Paperback / Softback
ISBN-10
3642079091
ISBN-13
9783642079092
Edition
Second Edition 2004
Publisher
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint
Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Country of Manufacture
GB
Country of Publication
GB
Publication Date
Dec 9th, 2010
Print length
538 Pages
Weight
792 grams
Dimensions
16.60 x 23.70 x 3.00 cms
Ksh 9,900.00
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Algorithmic design, especially for hard problems, is more essential for success in solving them than any standard improvement of current computer tech nologies.
Algorithmic design, especially for hard problems, is more essential for success in solving them than any standard improvement of current computer tech nologies. Because of this, the design of algorithms for solving hard problems is the core of current algorithmic research from the theoretical point of view as well as from the practical point of view. There are many general text books on algorithmics, and several specialized books devoted to particular approaches such as local search, randomization, approximation algorithms, or heuristics. But there is no textbook that focuses on the design of algorithms for hard computing tasks, and that systematically explains, combines, and compares the main possibilities for attacking hard algorithmic problems. As this topic is fundamental for computer science, this book tries to close this gap. Another motivation, and probably the main reason for writing this book, is connected to education. The considered area has developed very dynami cally in recent years and the research on this topic discovered several profound results, new concepts, and new methods. Some of the achieved contributions are so fundamental that one can speak about paradigms which should be in cluded in the education of every computer science student. Unfortunately, this is very far from reality. This is because these paradigms are not sufficiently known in the computer science community, and so they are insufficiently com municated to students and practitioners.
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