A Network-Flow Technique for Finding Low-Weight Bounded-Degree Spanning Trees

Sándor P. Fekete*, Samir Khuller, Monika Klemmstein, Balaji Raghavachari, Neal Young

*Corresponding author for this work

Research output: Contribution to journalArticle

38 Scopus citations

Abstract

Given a graph with edge weights satisfying the triangle inequality, and a degree bound for each vertex, the problem of computing a low-weight spanning tree such that the degree of each vertex is at most its specified bound is considered. In particular, modifying a given spanning tree T using adoptions to meet the degree constraints is considered. A novel network-flow-based algorithm for finding a good sequence of adoptions is introduced. The method yields a better performance guarantee than any previous algorithm. If the degree constraint d(v) for each v is at least 2, the algorithm is guaranteed to find a tree whose weight is at most the weight of the given tree times 2 - min{(d(v) - 2)/(degT(v) - 2):degT(v) > 2}, where degT(v) is the initial degree of v. Equally importantly, it takes this approach to the limit in the following sense: if any performance guarantee that is solely a function of the topology and edge weights of a given tree holds for any algorithm at all, then it also holds for the given algorithm. Examples are provided in which no lighter tree meeting the degree constraint exists. Linear-time algorithms are provided with the same worst-case performance guarantee. Choosing T to be a minimum spanning tree yields approximation algorithms with factors less than 2 for the general problem on geometric graphs with distances induced by various Lp norms. Finally, examples of Euclidean graphs are provided in which the ratio of the lengths of an optimal Traveling Salesman path and a minimum spanning tree can be arbitrarily close to 2.

Original languageEnglish (US)
Pages (from-to)310-324
Number of pages15
JournalJournal of Algorithms
Volume24
Issue number2
DOIs
StatePublished - Aug 1997

ASJC Scopus subject areas

  • Control and Optimization
  • Computational Mathematics
  • Computational Theory and Mathematics

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