Socially stable matchings in the hospitals/residents problem

  • Authors:

  • Georgios Askalidis;Nicole Immorlica;Augustine Kwanashie;David F. Manlove;Emmanouil Pountourakis

  • Affiliations:

  • Dept. of Electrical Engineering and Computer Science, Northwestern University;Dept. of Electrical Engineering and Computer Science, Northwestern University and Microsoft Research New England, UK;School of Computing Science, University of Glasgow, UK;School of Computing Science, University of Glasgow, UK;Dept. of Electrical Engineering and Computer Science, Northwestern University

  • Venue:
  • WADS'13 Proceedings of the 13th international conference on Algorithms and Data Structures
  • Year:
  • 2013

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Abstract

In the Hospitals/Residents (HR) problem, agents are partitioned into hospitals and residents. Each agent wishes to be matched to an agent (or agents) in the other set and has a strict preference over these potential matches. A matching is stable if there are no blocking pairs, i.e., no pair of agents that prefer each other to their assigned matches. Such a situation is undesirable as it could lead to a deviation in which the blocking pair form a private arrangement outside the matching. This however assumes that the blocking pair have social ties or communication channels to facilitate the deviation. Relaxing the stability definition to take account of the potential lack of social ties between agents can yield larger stable matchings. In this paper, we define the Hospitals/Residents problem under Social Stability (HRSS) which takes into account social ties between agents by introducing a social network graph to the HR problem. Edges in the social network graph correspond to resident-hospital pairs in the HR instance that know one another. Pairs that do not have corresponding edges in the social network graph can belong to a matching M but they can never block M. Relative to a relaxed stability definition for HRSS, called social stability, we show that socially stable matchings can have different sizes and the problem of finding a maximum socially stable matching is NP-hard, though approximable within 3/2. Furthermore we give polynomial time algorithms for special cases of the problem.