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Author Michail, Dimitrios
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Copyright Year ©2011
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Computer programming, programs & data
Subject Keyword Matchings ♦ Popularity ♦ Preferences
Abstract We experimentally study the problem of assigning applicants to posts. Each applicant provides a preference list, which may contain ties, ranking a subset of the posts. Different optimization criteria may be defined, which depend on the desired solution properties. The main focus of this work is to assess the quality of matchings computed by rank-maximal and popular matching algorithms and compare this with the minimum weight matching algorithm, which is a standard matching algorithm that is used in practice. Both rank-maximal and popular matching algorithms use common algorithmic techniques, which makes them excellent candidates for a running time comparison. Since popular matchings do not always exist, we also study the unpopularity of matchings computed by the aforementioned algorithms. Finally, extra criteria like total weight and cardinality are included, due to their importance in practice. All experiments are performed using structured random instances as well as instances created using real-world datasets.
ISSN 10846654
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2011-08-01
Publisher Place New York
e-ISSN 10846654
Journal Journal of Experimental Algorithmics (JEA)
Volume Number 16
Page Count 16
Starting Page 1.1
Ending Page 1.16


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Source: ACM Digital Library