dc.contributor |
Aalto-yliopisto |
fi |
dc.contributor |
Aalto University |
en |
dc.contributor.author |
Kangas, Kustaa |
|
dc.contributor.author |
Koivisto, Mikko |
|
dc.contributor.author |
Salonen, Sami |
|
dc.date.accessioned |
2020-01-02T13:56:15Z |
|
dc.date.available |
2020-01-02T13:56:15Z |
|
dc.date.issued |
2020-08-01 |
|
dc.identifier.citation |
Kangas , K , Koivisto , M & Salonen , S 2020 , ' A Faster Tree-Decomposition Based Algorithm for Counting Linear Extensions ' , Algorithmica , vol. 82 , no. 8 , pp. 2156-2173 . https://doi.org/10.1007/s00453-019-00633-1 |
en |
dc.identifier.issn |
0178-4617 |
|
dc.identifier.issn |
1432-0541 |
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dc.identifier.other |
PURE UUID: 3ad2a784-e533-4cf5-bea2-d07af2feb68e |
|
dc.identifier.other |
PURE ITEMURL: https://research.aalto.fi/en/publications/3ad2a784-e533-4cf5-bea2-d07af2feb68e |
|
dc.identifier.other |
PURE LINK: http://www.scopus.com/inward/record.url?scp=85074360704&partnerID=8YFLogxK |
|
dc.identifier.other |
PURE FILEURL: https://research.aalto.fi/files/38651339/Kangas2019_Article_AFasterTree_DecompositionBased_1.pdf |
|
dc.identifier.uri |
https://aaltodoc.aalto.fi/handle/123456789/41983 |
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dc.description.abstract |
We investigate the problem of computing the number of linear extensions of a given n-element poset whose cover graph has treewidth t. We present an algorithm that runs in time O~ (nt + 3) for any constant t; the notation O~ hides polylogarithmic factors. Our algorithm applies dynamic programming along a tree decomposition of the cover graph; the join nodes of the tree decomposition are handled by fast multiplication of multivariate polynomials. We also investigate the algorithm from a practical point of view. We observe that the running time is not well characterized by the parameters n and t alone: fixing these parameters leaves large variance in running times due to uncontrolled features of the selected optimal-width tree decomposition. We compare two approaches to select an efficient tree decomposition: one is to include additional features of the tree decomposition to build a more accurate, heuristic cost function; the other approach is to fit a statistical regression model to collected running time data.Both approaches are shown to yield a tree decomposition that typically is significantly more efficient than a random optimal-width tree decomposition. |
en |
dc.format.mimetype |
application/pdf |
|
dc.language.iso |
en |
en |
dc.publisher |
Springer New York |
|
dc.relation.ispartofseries |
Algorithmica |
en |
dc.rights |
openAccess |
en |
dc.title |
A Faster Tree-Decomposition Based Algorithm for Counting Linear Extensions |
en |
dc.type |
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä |
fi |
dc.description.version |
Peer reviewed |
en |
dc.contributor.department |
Department of Computer Science |
|
dc.contributor.department |
University of Helsinki |
|
dc.subject.keyword |
Algorithm selection |
|
dc.subject.keyword |
Empirical hardness |
|
dc.subject.keyword |
Linear extension |
|
dc.subject.keyword |
Multiplication of polynomials |
|
dc.subject.keyword |
Tree decomposition |
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dc.identifier.urn |
URN:NBN:fi:aalto-202001021094 |
|
dc.identifier.doi |
10.1007/s00453-019-00633-1 |
|
dc.type.version |
publishedVersion |
|