Permutation Pattern Matching for Doubly Partially Ordered Patterns

Authors Laurent Bulteau , Guillaume Fertin , Vincent Jugé, Stéphane Vialette

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Author Details

Laurent Bulteau
  • LIGM, CNRS, Univ Gustave Eiffel, F77454 Marne-la-Vallée, France
Guillaume Fertin
  • Nantes Université, LS2N (UMR 6004), CNRS, Nantes, France
Vincent Jugé
  • LIGM, CNRS, Univ Gustave Eiffel, F77454 Marne-la-Vallée, France
Stéphane Vialette
  • LIGM, CNRS, Univ Gustave Eiffel, F77454 Marne-la-Vallée, France

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Laurent Bulteau, Guillaume Fertin, Vincent Jugé, and Stéphane Vialette. Permutation Pattern Matching for Doubly Partially Ordered Patterns. In 33rd Annual Symposium on Combinatorial Pattern Matching (CPM 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 223, pp. 21:1-21:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)


We study in this paper the Doubly Partially Ordered Pattern Matching (or DPOP Matching) problem, a natural extension of the Permutation Pattern Matching problem. Permutation Pattern Matching takes as input two permutations σ and π, and asks whether there exists an occurrence of σ in π; whereas DPOP Matching takes two partial orders P_v and P_p defined on the same set X and a permutation π, and asks whether there exist |X| elements in π whose values (resp., positions) are in accordance with P_v (resp., P_p). Posets P_v and P_p aim at relaxing the conditions formerly imposed by the permutation σ, since σ yields a total order on both positions and values. Our problem being NP-hard in general (as Permutation Pattern Matching is), we consider restrictions on several parameters/properties of the input, e.g., bounding the size of the pattern, assuming symmetry of the posets (i.e., P_v and P_p are identical), assuming that one partial order is a total (resp., weak) order, bounding the length of the longest chain/anti-chain in the posets, or forbidding specific patterns in π. For each such restriction, we provide results which together give a(n almost) complete landscape for the algorithmic complexity of the problem.

Subject Classification

ACM Subject Classification
  • Theory of computation → Design and analysis of algorithms
  • Partial orders
  • Permutations
  • Pattern Matching
  • Algorithmic Complexity
  • Parameterized Complexity


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