Algorithmics for hard problems : introduction to combinatorial optimization, randomization, approximation, and heuristics
著者
書誌事項
Algorithmics for hard problems : introduction to combinatorial optimization, randomization, approximation, and heuristics
（Texts in theoretical computer science, An EATCS series）
Springer, 2004
2nd ed, [corrected printing]
- : softcover
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注記
Includes bibliographical references (p. [503]-524) and index
"Corrected printing 2004"--T.p. verso
内容説明・目次
内容説明
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.
目次
1 Introduction.- 2 Elementary Fundamentals.- 3 Deterministic Approaches.- 4 Approximation Algorithms.- 5 Randomized Algorithms.- 6 Heuristics.- 7 A Guide to Solving Hard Problems.- References.
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