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Iterative Methods in Combinatorial Optimization / Lap Chi Lau, R. Ravi, Mohit Singh.

By: Contributor(s): Material type: TextTextSeries: Cambridge Texts in Applied Mathematics ; 46 | Cambridge Texts in Applied Mathematics ; 46.Publisher: Cambridge : Cambridge University Press, 2011Description: 1 online resource (256 pages) : digital, PDF file(s)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9780511977152 (ebook)
Subject(s): Additional physical formats: Print version: : No titleDDC classification:
  • 518/.26 22
LOC classification:
  • QA297.8 .L38 2011
Online resources: Summary: 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.
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Title from publisher's bibliographic system (viewed on 04 Apr 2016).

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.

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