Overview
- The technique-oriented approach provides a unified view of the design techniques for approximation algorithms
- Detailed algorithms, as well as complete proofs and analyses, are presented for each technique
- Numerous examples help the reader to better understand the design and analysis techniques
- Collects a great number of applications, many from recent research papers
- Includes a large collection of approximation algorithms of geometric problems
- Includes supplementary material: sn.pub/extras
Part of the book series: Springer Optimization and Its Applications (SOIA, volume 62)
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Table of contents (10 chapters)
Keywords
About this book
Reviews
From the reviews:
“This book is intended for graduate courses of different levels, and course plans based on different chapter selections are proposed. Each chapter is accompanied by several pages of exercises and historical notes, setting the material and the references in context. The comprehensive bibliography covers a huge amount of literature in the heuristics and approximations area, as well as specific application problems. The index is detailed. This makes the book a good source for a course on approximation algorithms. ...For the more advanced reader the book seems to be an excellent in-depth resource on approximation algorithms, for their beginning up to the latest developments.”
—Gudula Runger, Computing Reviews
“It contains a large amount of precisely selected topics covering various aspects and design techniques related to approximation algorithms. … It has been intended as a textbook for a graduate course in theoretical computer science. … it can also be used as a reference book for postgraduate students and researchers in the area of design and analysis of algorithms. It also serves as a reference for established researchers by providing efficient tools for various applied areas like applied mathematics, engineering, medicine, economics, and other sciences.” (Vladimír Lacko, Zentralblatt MATH, Vol. 1237, 2012)
“This textbook organizes approximation algorithms into chapters based on the design techniques. … this book is particularly suited for students who, possibly starting from scratch, want to first encounter, then absorb, and finally master the main techniques which have emerged as general paradigms in the design of approximation algorithms. This includes self-study by novices … but also teaching by experts in standard courses.” (Romeo Rizzi, Mathematical Reviews, January, 2013)
Authors and Affiliations
About the authors
Ding-Zhu Du is co-editor of the first and soon-to-be published, second editions, of the Handbook of Combinatorial Optimization. He was also co-author with P.M. Pardalos and W. Wu of the Kluwer publication "Mathematical Theory of Optimization". Du will co-author upcoming Springer publications (2012) entitled "Connected Dominating Set: Theory and Applications" and "Introduction to Combinatorial Optimization". Prof. Du is also the EiC of the Journal of Combinatorial Optimization (Springer).
Ker-I Ko is a well known expert in the field of theoretical computer science. He has authored a single publication with Birkhauser "Computational Complexity of Real Functions" in 1991, with very good reviews. Prof. Du and Ker-I Ko have written several texts together including "Problem Solving in Automata, Languages, and Complexity" John Wiley, 2001; "Theory of Computational Complexity", John Wiley, 2000; Both of these books have received good reviews.
Xiaodong Hu is an expert in combinatorial optimization. He is a member of the editorial boards of Journal of Combinatorial Optimization and Discrete Mathematics, Algorithms and Applications.
Bibliographic Information
Book Title: Design and Analysis of Approximation Algorithms
Authors: Ding-Zhu Du, Ker-I Ko, Xiaodong Hu
Series Title: Springer Optimization and Its Applications
DOI: https://doi.org/10.1007/978-1-4614-1701-9
Publisher: Springer New York, NY
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Science+Business Media, LLC 2012
Hardcover ISBN: 978-1-4614-1700-2Published: 17 November 2011
Softcover ISBN: 978-1-4899-9844-6Published: 25 January 2014
eBook ISBN: 978-1-4614-1701-9Published: 18 November 2011
Series ISSN: 1931-6828
Series E-ISSN: 1931-6836
Edition Number: 1
Number of Pages: XII, 440
Topics: Optimization, Algorithm Analysis and Problem Complexity