Analysis of Approximation Algorithms for k-Set Cover Using Factor-Revealing Linear Programs

  • Stavros Athanassopoulos
  • Ioannis Caragiannis
  • Christos Kaklamanis
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4639)


We present new combinatorial approximation algorithms for k-set cover. Previous approaches are based on extending the greedy algorithm by efficiently handling small sets. The new algorithms further extend them by utilizing the natural idea of computing large packings of elements into sets of large size. Our results improve the previously best approximation bounds for the k-set cover problem for all values of k ≥ 6. The analysis technique could be of independent interest; the upper bound on the approximation factor is obtained by bounding the objective value of a factor-revealing linear program.


Local Search Approximation Algorithm Greedy Algorithm Approximation Ratio Local Search Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Stavros Athanassopoulos
    • 1
  • Ioannis Caragiannis
    • 1
  • Christos Kaklamanis
    • 1
  1. 1.Research Academic Computer Technology Institute &, Department of Computer Engineering and Informatics, University of Patras, 26500 RioGreece

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