Social Welfare in One-Sided Matchings: Random Priority and Beyond

  • Aris Filos-Ratsikas
  • Søren Kristoffer Stiil Frederiksen
  • Jie Zhang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8768)


We study the problem of approximate social welfare maximization (without money) in one-sided matching problems when agents have unrestricted cardinal preferences over a finite set of items. Random priority is a very well-known truthful-in-expectation mechanism for the problem. We prove that the approximation ratio of random priority is Θ(n − 1/2) while no truthful-in-expectation mechanism can achieve an approximation ratio better than O(n − 1/2), where n is the number of agents and items. Furthermore, we prove that the approximation ratio of all ordinal (not necessarily truthful-in-expectation) mechanisms is upper bounded by O(n − 1/2), indicating that random priority is asymptotically the best truthful-in-expectation mechanism and the best ordinal mechanism for the problem.


Social Welfare Social Choice Approximation Ratio Valuation Function Social Choice Function 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Aris Filos-Ratsikas
    • 1
  • Søren Kristoffer Stiil Frederiksen
    • 1
  • Jie Zhang
    • 2
  1. 1.Department of Computer ScienceAarhus UniversityDenmark
  2. 2.Department of Computer ScienceUniversity of OxfordUK

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