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5 - Thin Trees and Random Trees

Published online by Cambridge University Press:  14 November 2024

Vera Traub
Affiliation:
University of Bonn
Jens Vygen
Affiliation:
University of Bonn
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Summary

After the O(log n)-approximation algorithms for Asymmetric TSP, the first algorithm to beat the cycle cover algorithm by more than a constant factor was found in 2009 by Asadpour, Goemans, Mądry, Oveis Gharan, and Saberi. Their approach is based on finding a "thin" (oriented) spanning tree and then adding edges to obtain a tour. A major open question is how thin trees are guaranteed to exist.

The O(log n/loglog n)-approximation algorithm by Asadpour et al. samples a random spanning tree from the maximum entropy distribution. To show how this works, we discuss interesting connections between random spanning trees and electrical networks. Some results of this chapter will be used again in Chapters 10 and 11.

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Publisher: Cambridge University Press
Print publication year: 2024

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  • Thin Trees and Random Trees
  • Vera Traub, University of Bonn, Jens Vygen, University of Bonn
  • Book: Approximation Algorithms for Traveling Salesman Problems
  • Online publication: 14 November 2024
  • Chapter DOI: https://doi.org/10.1017/9781009445436.006
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  • Thin Trees and Random Trees
  • Vera Traub, University of Bonn, Jens Vygen, University of Bonn
  • Book: Approximation Algorithms for Traveling Salesman Problems
  • Online publication: 14 November 2024
  • Chapter DOI: https://doi.org/10.1017/9781009445436.006
Available formats
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Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • Thin Trees and Random Trees
  • Vera Traub, University of Bonn, Jens Vygen, University of Bonn
  • Book: Approximation Algorithms for Traveling Salesman Problems
  • Online publication: 14 November 2024
  • Chapter DOI: https://doi.org/10.1017/9781009445436.006
Available formats
×