Algorithmics for hard problems : introduction to combinatorial optimization, randomization, approximation, and heuristics
Author(s)
Bibliographic Information
Algorithmics for hard problems : introduction to combinatorial optimization, randomization, approximation, and heuristics
（Texts in theoretical computer science, An EATCS series）
Springer, c2003
2nd ed
Available at / 17 libraries
-
The University of Electro-Communications Library研
549.98/H97,548.964/H972002106612,2003100639,2003102294
-
No Libraries matched.
- Remove all filters.
Note
Includes bibliographical references (p. [511]-532) and index
Description and Table of Contents
Description
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.
Table of Contents
1 Introduction.- 2 Elementary Fundamentals.- 3 Deterministic Approaches.- 4 Approximation Algorithms.- 5 Randomized Algorithms.- 6 Heuristics.- 7 A Guide to Solving Hard Problems.- References.
by "Nielsen BookData"