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Algorithmics for Hard Problems

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Juraj Hromkovic 作者
Springer
譯者
2002-11-19 出版日期
544 頁數
USD 64.95 價格
Hardcover
叢書系列
9783540441342 圖書編碼

Algorithmics for Hard Problems 在線電子書 圖書標籤: 算法  計算機科學  Algorithmics  TCS  計算機  for  algorithm  Problems   


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Algorithmics for Hard Problems 在線電子書 epub 下載 mobi 下載 pdf 下載 txt 下載 2024

Algorithmics for Hard Problems 在線電子書 epub 下載 pdf 下載 mobi 下載 txt 下載 2024

Algorithmics for Hard Problems 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024



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Algorithmics for Hard Problems 在線電子書 圖書描述

There are several approaches to attack hard problems. All have their merits, but also their limitations, and need a large body of theory as their basis. A number of books for each one exist: books on complexity theory, others on approximation algorithms, heuristic approaches, parametrized complexity, and yet others on randomized algorithms. This book discusses thoroughly all of the above approaches. And, amazingly, at the same time, does this in a style that makes the book accessible not only to theoreticians, but also to the non-specialist, to the student or teacher, and to the programmer. Do you think that mathematical rigor and accessibility contradict? Look at this book to find out that they do not, due to the admirable talent of the author to present his material in a clear and concise way, with the idea behind the approach spelled out explicitly, often with a revealing example.Reading this book is a beautiful experience and I can highly recommend it to anyone interested in learning how to solve hard problems. It is not just a condensed union of material from other books. Because it discusses the different approaches in depth, it has the chance to compare them in detail, and, most importantly, to highlight under what circumstances which approach might be worth exploring. No book on a single type of solution can do that, but this book does it in an absolutely fascinating way that can serve as a pattern for theory textbooks with a high level of generality. (Peter Widmayer)The second edition extends the part on the method of relaxation to linear programming with an emphasis on rounding, LP-duality, and primal-dual schema, and provides a self-contained and transparent presentation of the design of randomized algorithms for primality testing.

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