Abstract
Hypertree width is a similar notion to treewidth, also with many equivalent characterizations and many applications. If the hypertree widths of constraint graphs of instances of Constraint Satisfaction Problems (CSPs) are bounded by a constant, the relevant constraint satisfaction problems are tractable. In this paper, we show that with high probability, hypertree width is large on sparse random k-uniform hypergraphs. Our results provide further theoretical evidence on hardness of some random constraint satisfaction problems, called Model RB and Model RD, around the satisfiability phase transition points.
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Wang, C., Liu, T., Xu, K. (2013). Large Hypertree Width for Sparse Random Hypergraphs. In: Fellows, M., Tan, X., Zhu, B. (eds) Frontiers in Algorithmics and Algorithmic Aspects in Information and Management. Lecture Notes in Computer Science, vol 7924. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38756-2_30
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DOI: https://doi.org/10.1007/978-3-642-38756-2_30
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