<div class="csl-bib-body">
<div class="csl-entry">Gottlob, G., Okulmus, C., & Pichler, R. (2022). Fast and parallel decomposition of constraint satisfaction problems. <i>Constraints</i>, <i>27</i>, 284–326. https://doi.org/10.1007/s10601-022-09332-1</div>
</div>
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dc.identifier.issn
1383-7133
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/139811
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dc.description.abstract
Constraint Satisfaction Problems (CSP) are notoriously hard. Consequently, powerful decomposition methods have been developed to overcome this complexity. However, this poses the challenge of actually computing such a decomposition for a given CSP instance, and previous algorithms have shown their limitations in doing so. In this paper, we present a number of key algorithmic improvements and parallelisation techniques to compute so-called Generalized Hypertree Decompositions (GHDs) faster. We thus advance the ability to compute optimal (i.e., minimal-width) GHDs for a significantly wider range of CSP instances on modern machines. This lays the foundation for more systems and applications in evaluating CSPs and related problems (such as Conjunctive Query answering) based on their structural properties.
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dc.description.sponsorship
Fonds zur Förderung der wissenschaftlichen Forschung (FWF)
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dc.language.iso
en
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dc.publisher
SPRINGER
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dc.relation.ispartof
Constraints
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dc.subject
Constraint satisfaction
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dc.subject
Hypergraphs
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dc.subject
Parallel computing
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dc.subject
Structural decomposition methods
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dc.title
Fast and parallel decomposition of constraint satisfaction problems
