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Documents authored by Cooper, Frances

Document
DOI: 10.4230/LIPIcs.SEA.2020.20
Algorithms for New Types of Fair Stable Matchings

Authors: Frances Cooper and David Manlove

Published in: LIPIcs, Volume 160, 18th International Symposium on Experimental Algorithms (SEA 2020)

Abstract
We study the problem of finding "fair" stable matchings in the Stable Marriage problem with Incomplete lists (SMI). For an instance I of SMI there may be many stable matchings, providing significantly different outcomes for the sets of men and women. We introduce two new notions of fairness in SMI. Firstly, a regret-equal stable matching minimises the difference in ranks of a worst-off man and a worst-off woman, among all stable matchings. Secondly, a min-regret sum stable matching minimises the sum of ranks of a worst-off man and a worst-off woman, among all stable matchings. We present two new efficient algorithms to find stable matchings of these types. Firstly, the Regret-Equal Degree Iteration Algorithm finds a regret-equal stable matching in O(d₀ nm) time, where d₀ is the absolute difference in ranks between a worst-off man and a worst-off woman in the man-optimal stable matching, n is the number of men or women, and m is the total length of all preference lists. Secondly, the Min-Regret Sum Algorithm finds a min-regret sum stable matching in O(d_s m) time, where d_s is the difference in the ranks between a worst-off man in each of the woman-optimal and man-optimal stable matchings. Experiments to compare several types of fair optimal stable matchings were conducted and show that the Regret-Equal Degree Iteration Algorithm produces matchings that are competitive with respect to other fairness objectives. On the other hand, existing types of "fair" stable matchings did not provide as close an approximation to regret-equal stable matchings.
Cite as

Frances Cooper and David Manlove. Algorithms for New Types of Fair Stable Matchings. In 18th International Symposium on Experimental Algorithms (SEA 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 160, pp. 20:1-20:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{cooper_et_al:LIPIcs.SEA.2020.20,
  author =	{Cooper, Frances and Manlove, David},
  title =	{{Algorithms for New Types of Fair Stable Matchings}},
  booktitle =	{18th International Symposium on Experimental Algorithms (SEA 2020)},
  pages =	{20:1--20:13},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-148-1},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{160},
  editor =	{Faro, Simone and Cantone, Domenico},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2020.20},
  URN =		{urn:nbn:de:0030-drops-120945},
  doi =		{10.4230/LIPIcs.SEA.2020.20},
  annote =	{Keywords: Stable marriage, Algorithms, Optimality, Fair stable matchings, Regret-equality, Min-regret sum}
}
Document
DOI: 10.4230/LIPIcs.SEA.2018.8
A 3/2-Approximation Algorithm for the Student-Project Allocation Problem

Authors: Frances Cooper and David Manlove

Published in: LIPIcs, Volume 103, 17th International Symposium on Experimental Algorithms (SEA 2018)

Abstract
The Student-Project Allocation problem with lecturer preferences over Students (SPA-S) comprises three sets of agents, namely students, projects and lecturers, where students have preferences over projects and lecturers have preferences over students. In this scenario we seek a stable matching, that is, an assignment of students to projects such that there is no student and lecturer who have an incentive to deviate from their assignee/s. We study SPA-ST, the extension of SPA-S in which the preference lists of students and lecturers need not be strictly ordered, and may contain ties. In this scenario, stable matchings may be of different sizes, and it is known that MAX SPA-ST, the problem of finding a maximum stable matching in SPA-ST, is NP-hard. We present a linear-time 3/2-approximation algorithm for MAX SPA-ST and an Integer Programming (IP) model to solve MAX SPA-ST optimally. We compare the approximation algorithm with the IP model experimentally using randomly-generated data. We find that the performance of the approximation algorithm easily surpassed the 3/2 bound, constructing a stable matching within 92% of optimal in all cases, with the percentage being far higher for many instances.
Cite as

Frances Cooper and David Manlove. A 3/2-Approximation Algorithm for the Student-Project Allocation Problem. In 17th International Symposium on Experimental Algorithms (SEA 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 103, pp. 8:1-8:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{cooper_et_al:LIPIcs.SEA.2018.8,
  author =	{Cooper, Frances and Manlove, David},
  title =	{{A 3/2-Approximation Algorithm for the Student-Project Allocation Problem}},
  booktitle =	{17th International Symposium on Experimental Algorithms (SEA 2018)},
  pages =	{8:1--8:13},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-070-5},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{103},
  editor =	{D'Angelo, Gianlorenzo},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2018.8},
  URN =		{urn:nbn:de:0030-drops-89439},
  doi =		{10.4230/LIPIcs.SEA.2018.8},
  annote =	{Keywords: Matching problems, Approximation, Algorithms, Stability}
}
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