Design and Analysis of Approximation Algorithms

Unlike other books on theoretical computer science, this textbook organizes approximation algorithms into chapters based on the design techniques for the algorithms. This allows the reader to study approximation algorithms of the same nature together.

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.

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

Autorentext

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.

Klappentext
When precise algorithmic solutions are difficult to compute, the use of approximation algorithms can help. Design and Analysis of Approximation Algorithms is a textbook for a graduate course in theoretical computer science taught globally in universities. It can also be used as a reference work for researchers in the area of design and analysis algorithms.

There are few texts available for this standard course, and those that do exist mainly follow a problem-oriented format. This text follows a structured, technique-oriented presentation. Approximation algorithms are organized into chapters based on the design techniques for the algorithms, enabling the reader to study algorithms of the same nature with ease, and providing an improved understanding of the design and analysis techniques for approximation algorithms. Instructors benefit from this approach allowing for an easy way to present the ideas and techniques of algorithms with a unified approach.

Inhalt
Preface.- 1. Introduction.- 2. Greedy Strategy.- 3. Restriction.- 4. Partition.- 5. Guillotine Cut.- 6. Relaxation.- 7. Linear Programming.- 8. Primal-Dual Scheme and Local Ratio.- 9. Semidefinite Programming.- 10. Inapproximability.- Bibliography.- Index.