Iterative Methods in Combinatorial Optimization
With the advent of approximation algorithms for NP-hard combinatorial optimization problems, several techniques from exact optimization such as the primal-dual method have proven their staying power and versatility. This book describes a simple and powerful method that is iterative in essence, and similarly useful in a variety of settings for exact and approximate optimization. The authors highlight the commonality and uses of this method to prove a variety of classical polyhedral results on matchings, trees, matroids, and flows. The presentation style is elementary enough to be accessible to anyone with exposure to basic linear algebra and graph theory, making the book suitable for introductory courses in combinatorial optimization at the upper undergraduate and beginning graduate levels. Discussions of advanced applications illustrate their potential for future application in research in approximation algorithms.
- Presents a unified way of looking at several problems
- Offers new ways of deriving classical results in optimization
- Provides extensions to hard variants of classical problems
- Offers elementary presentation appealing to a broad mathematically interested audience
Product details
April 2011Paperback
9780521189439
256 pages
229 × 153 × 15 mm
0.36kg
44 b/w illus. 102 exercises
Available
Table of Contents
- 1. Introduction
- 2. Preliminaries
- 3. Matching and vertex cover in bipartite graphs
- 4. Spanning trees
- 5. Matroids
- 6. Arborescence and rooted connectivity
- 7. Submodular flows and applications
- 8. Network matrices
- 9. Matchings
- 10. Network design
- 11. Constrained optimization problems
- 12. Cut problems
- 13. Iterative relaxation: early and recent examples
- 14. Summary.