Design and Analysis of Approximation Algorithms (Springer Optimization and Its Applications) recent book reviews

Book Description:

Series: Springer Optimization and Its Applications (Book 62)
Paperback: 440 pages
Publisher: Springer; 2012 edition (January 26, 2014)
Language: English
ISBN-10: 1489998446
ISBN-13: 978-1489998446
Product Dimensions:
6.1 x 1 x 9.2 inches
Shipping Weight: 1.4 pounds (View shipping rates and policies)
Book market health care finance: basic tools for nonfinancial managers (health care finance (baker))Average Customer Review:
5.0 out of 5 stars See all reviews (1 customer review)

Book Details:

This book is intended to be used as a textbook for graduate students studying theoretical computer science. It can also be used as a reference book for researchers in the area of design and analysis of approximation algorithms. Design and Analysis of Approximation Algorithms is a graduate course in theoretical computer science taught widely in the universities, both in the United States and abroad. There are, however, very few textbooks available for this course. Among those available in the market, most books follow a problem-oriented format; that is, they collected many important combinatorial optimization problems and their approximation algorithms, and organized them based on the types, or applications, of problems, such as geometric-type problems, algebraic-type problems, etc. Such arrangement of materials is perhaps convenient for a researcher to look for the problems and algorithms related to his/her work, but is difficult for a student to capture the ideas underlying the various algorithms. In the new book proposed here, we follow a more structured, technique-oriented presentation. We organize approximation algorithms into different chapters, based on the design techniques for the algorithms, so that the reader can study approximation algorithms of the same nature together. It helps the reader to better understand the design and analysis techniques for approximation algorithms, and also helps the teacher to present the ideas and techniques of approximation algorithms in a more unified way.

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