English

Finding Optimal Triangulations Parameterized by Edge Clique Cover

Data Structures and Algorithms 2022-02-08 v3 Discrete Mathematics

Abstract

We consider problems that can be formulated as a task of finding an optimal triangulation of a graph w.r.t. some notion of optimality. We present algorithms parameterized by the size of a minimum edge clique cover (cccc) to such problems. This parameterization occurs naturally in many problems in this setting, e.g., in the perfect phylogeny problem cccc is at most the number of taxa, in fractional hypertreewidth cccc is at most the number of hyperedges, and in treewidth of Bayesian networks cccc is at most the number of non-root nodes. We show that the number of minimal separators of graphs is at most 2cc2^{cc}, the number of potential maximal cliques is at most 3cc3^{cc}, and these objects can be listed in times O(2cc)O^*(2^{cc}) and O(3cc)O^*(3^{cc}), respectively, even when no edge clique cover is given as input; the O()O^*(\cdot) notation omits factors polynomial in the input size. These enumeration algorithms imply O(3cc)O^*(3^{cc}) time algorithms for problems such as treewidth, weighted minimum fill-in, and feedback vertex set. For generalized and fractional hypertreewidth we give O(4m)O^*(4^m) time and O(3m)O^*(3^m) time algorithms, respectively, where mm is the number of hyperedges. When an edge clique cover of size cccc' is given as a part of the input we give O(2cc)O^*(2^{cc'}) time algorithms for treewidth, minimum fill-in, and chordal sandwich. This implies an O(2n)O^*(2^n) time algorithm for perfect phylogeny, where nn is the number of taxa. We also give polynomial space algorithms with time complexities O(9cc)O^*(9^{cc'}) and O(9cc+O(log2cc))O^*(9^{cc + O(\log^2 cc)}) for problems in this framework.

Keywords

Cite

@article{arxiv.1912.10989,
  title  = {Finding Optimal Triangulations Parameterized by Edge Clique Cover},
  author = {Tuukka Korhonen},
  journal= {arXiv preprint arXiv:1912.10989},
  year   = {2022}
}

Comments

28 pages, 3 figures, appeared in IPEC'20, to appear in Algorithmica special issue of IPEC'20

R2 v1 2026-06-23T12:54:55.489Z