Algorithmica

, Volume 65, Issue 3, pp 498–516 | Cite as

Improved Approximation Algorithms for the Spanning Star Forest Problem

  • Ning Chen
  • Roee Engelberg
  • C. Thach Nguyen
  • Prasad Raghavendra
  • Atri Rudra
  • Gyanit Singh
Article

Abstract

A star graph is a tree of diameter at most two. A star forest is a graph that consists of node-disjoint star graphs. In the spanning star forest problem, given an unweighted graph G, the objective is to find a star forest that contains all vertices of G and has the maximum number of edges. This problem is the complement of the dominating set problem in the following sense: On a graph with n vertices, the size of the maximum spanning star forest is equal to n minus the size of the minimum dominating set.

We present a 0.71-approximation algorithm for this problem, improving upon the approximation factor of 0.6 of Nguyen et al. (SIAM J. Comput. 38:946–962, 2008). We also present a 0.64-approximation algorithm for the problem on node-weighted graphs. Finally, we present improved hardness of approximation results for the weighted (both edge-weighted and node-weighted) versions of the problem.

Our algorithms use a non-linear rounding scheme, which might be of independent interest.

Keywords

Approximation algorithms Spanning star forest problem 

Notes

Acknowledgement

We thank Aravind Srinivasan for clarifying the status of the approximability of the weighted set cover problem.

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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Ning Chen
    • 1
  • Roee Engelberg
    • 2
  • C. Thach Nguyen
    • 3
  • Prasad Raghavendra
    • 4
  • Atri Rudra
    • 5
  • Gyanit Singh
    • 3
  1. 1.Division of Mathematical Sciences, School of Physical and Mathematical SciencesNanyang Technological UniversitySingaporeSingapore
  2. 2.Department of Computer ScienceTechnionHaifaIsrael
  3. 3.Department of Computer Science & EngineeringUniversity of WashingtonSeattleUSA
  4. 4.School of Computer ScienceGeorgia Institute of TechnologyAtlantaUSA
  5. 5.Department of Computer Science & EngineeringUniversity at Buffalo, State University of New YorkBuffaloUSA

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