Mathematical Programming

, Volume 152, Issue 1–2, pp 147–188

Efficient cost-sharing mechanisms for prize-collecting problems

  • A. Gupta
  • J. Könemann
  • S. Leonardi
  • R. Ravi
  • G. Schäfer
Full Length Paper Series A


We consider the problem of designing efficient mechanisms to share the cost of providing some service to a set of self-interested customers. In this paper, we mainly focus on cost functions that are induced by prize-collecting optimization problems. Such cost functions arise naturally whenever customers can be served in two different ways: either by being part of a common service solution or by being served individually. One of our main contributions is a general lifting technique that allows us to extend the social cost approximation guarantee of a Moulin mechanism for the respective non-prize-collecting problem to its prize-collecting counterpart. Our lifting technique also suggests a generic design template to derive Moulin mechanisms for prize-collecting problems. The approach is particularly suited for cost-sharing methods that are based on primal-dual algorithms. We illustrate the applicability of our approach by deriving Moulin mechanisms for prize-collecting variants of submodular cost-sharing, facility location and Steiner forest problems. All our mechanisms are essentially best possible with respect to budget balance and social cost approximation guarantees. Finally, we show that the Moulin mechanism by Könemann et al. (SIAM J Comput 37(5):1319–1341, 2008) for the Steiner forest problem is \(O(\log ^3 k)\)-approximate. Our approach adds a novel methodological contribution to existing techniques by showing that such a result can be proved by embedding the graph distances into random hierarchically separated trees.

Mathematics Subject Classification

90C27 68R99 91A10 

Copyright information

© Springer-Verlag Berlin Heidelberg and Mathematical Optimization Society 2014

Authors and Affiliations

  • A. Gupta
    • 1
  • J. Könemann
    • 2
  • S. Leonardi
    • 3
  • R. Ravi
    • 4
  • G. Schäfer
    • 5
    • 6
  1. 1.School of Computer ScienceCarnegie Mellon UniversityPittsburghUSA
  2. 2.Department of Combinatorics and OptimizationUniversity of WaterlooWaterlooCanada
  3. 3.Department of Computer, Control and Management Engineering ‘Antonio Ruberti’Sapienza University of RomeRomeItaly
  4. 4.Tepper School of BusinessCarnegie Mellon UniversityPittsburghUSA
  5. 5.Networks and Optimization GroupCentrum Wiskunde & Informatica (CWI)AmsterdamThe Netherlands
  6. 6.Department of Econometrics and Operations ResearchVU University AmsterdamAmsterdamThe Netherlands

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