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PACE Solver Description: DreyFVS

Authors Gabriel Bathie, Gaétan Berthe, Yoann Coudert-Osmont, David Desobry, Amadeus Reinald , Mathis Rocton



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Author Details

Gabriel Bathie
  • École Normale Supérieure de Lyon, France
Gaétan Berthe
  • École Normale Supérieure de Lyon, France
Yoann Coudert-Osmont
  • Université de Lorraine, CNRS, Inria, LORIA, Nancy, France
David Desobry
  • Université de Lorraine, CNRS, Inria, LORIA, Nancy, France
Amadeus Reinald
  • École Normale Supérieure de Lyon, France
Mathis Rocton
  • École Normale Supérieure de Lyon, France

Cite AsGet BibTex

Gabriel Bathie, Gaétan Berthe, Yoann Coudert-Osmont, David Desobry, Amadeus Reinald, and Mathis Rocton. PACE Solver Description: DreyFVS. In 17th International Symposium on Parameterized and Exact Computation (IPEC 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 249, pp. 31:1-31:4, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2022)
https://doi.org/10.4230/LIPIcs.IPEC.2022.31

Abstract

We describe DreyFVS, a heuristic for Directed Feedback Vertex Set submitted to the 2022 edition of Parameterized Algorithms and Computational Experiments Challenge. The Directed Feedback Vertex Set problem asks to remove a minimal number of vertices from a digraph such that the resulting digraph is acyclic. Our algorithm first performs a guess on a reduced instance by leveraging the Sinkhorn-Knopp algorithm, to then improve this solution by pipelining two local search methods.

Subject Classification

ACM Subject Classification
  • Theory of computation → Graph algorithms analysis
  • Theory of computation → Parameterized complexity and exact algorithms
Keywords
  • Directed Feedback Vertex Set
  • Heuristic
  • Sinkhorn algorithm
  • Local search

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References

  1. Gabriel Bathie, Gaétan Berthe, Yoann Coudert-Osmont, David Desobry, Amadeus Reinald, and Mathis Rocton. DreyFVS, June 2022. URL: https://doi.org/10.5281/zenodo.6638217.
  2. Isabel Beichl and Francis Sullivan. Approximating the permanent via importance sampling with application to the dimer covering problem. Journal of Computational Physics, 149(1):128-147, 1999. URL: https://doi.org/10.1006/jcph.1998.6149.
  3. Philippe Galinier, Eunice Lemamou, and Mohamed Wassim Bouzidi. Applying local search to the feedback vertex set problem. Journal of Heuristics, 19(5):797-818, October 2013. URL: https://doi.org/10.1007/s10732-013-9224-z.
  4. Hen-Ming Lin and Jing-Yang Jou. On computing the minimum feedback vertex set of a directed graph by contraction operations. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 19(3):295-307, 2000. URL: https://doi.org/10.1109/43.833199.
  5. James Shook and Isabel Beichl. Matrix scaling: A new heuristic for the feedback vertex set problem, June 2014. URL: https://math.nist.gov/mcsd/Seminars/2014/2014-06-10-Shook-presentation.pdf.
  6. Richard Sinkhorn and Paul Knopp. Concerning nonnegative matrices and doubly stochastic matrices. Pacific Journal of Mathematics, 21(2):343-348, 1967. Google Scholar
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