Social welfare in one-sided matchings: random priority and beyond

Aris Filos-Ratsikas, Soren Kristoffer Stiil Frederiksen, Jie Zhang

Research output: Chapter or section in a book/report/conference proceedingChapter in a published conference proceeding

55 Citations (SciVal)


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 O(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.
Original languageEnglish
Title of host publicationAlgorithmic Game Theory
EditorsR Lavi
Place of PublicationSwitzerland
Number of pages12
ISBN (Print)978-3-662-44802-1
Publication statusPublished - 2014

Publication series

NameLecture Notes in Computer Science

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