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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao zbMATH Openarrow_drop_down
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Article
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SIAM Journal on Computing
Article . 1986 . Peer-reviewed
Data sources: Crossref
DBLP
Article . 1986
Data sources: DBLP
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The Complexity of Counting Stable Marriages

The complexity of counting stable marriages
Authors: Robert W. Irving; Paul Leather;

The Complexity of Counting Stable Marriages

Abstract

In an instance of size n of the stable marriage problem, each of n men and n women ranks the members of the opposite sex in order to preference. A stable matching is a complete matching of men and women such that no man and woman who are not partners both prefer each other to their actual partners under the matching. It is well known that the least one stable matching exists for every stable marriage instance, so that the decision version of the problem always has a ''yes'' answer. Furthermore, efficient algorithms are known for the determination of such a stable matching, so that the search version of the problem is polynomially solvable. However, by exploring the structure of the set of stable matchings for any particular instance of the problem, and exploiting its relationship with the set of antichains of an associated partially ordered set, we prove that the enumeration version of the problem - determining the number of stable matchings - is {\#}P-complete, and therefore cannot be solved in polynomial time if \(P\neq NP\).

Keywords

Permutations, words, matrices, Analysis of algorithms and problem complexity, stable matching, stable marriage problem

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
150
Top 1%
Top 1%
Top 10%
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