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PACE Solver Description: LUNCH - Linear Uncrossing Heuristics

Authors Kenneth Langedal , Matthias Bentert, Thorgal Blanco , Pål Grønås Drange

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Subject Classification

ACM Subject Classification
  • Theory of computation → Design and analysis of algorithms
Keywords
  • graph drawing
  • feedback arc set
  • algorithm engineering

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Abstract

The 2024 PACE challenge is on One-Sided Crossing Minimization: Given a bipartite graph with one fixed and one free layer, compute an ordering of the vertices in the free layer that minimizes the number of edge crossings in a straight-line drawing of the graph. Here, we briefly describe our exact, parameterized, and heuristic submissions. The main contribution is an efficient reduction to a weighted version of Directed Feedback Arc Set, allowing us to detect subproblems that can be solved independently.

Cite As Get BibTex

Kenneth Langedal, Matthias Bentert, Thorgal Blanco, and Pål Grønås Drange. PACE Solver Description: LUNCH - Linear Uncrossing Heuristics. In 19th International Symposium on Parameterized and Exact Computation (IPEC 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 321, pp. 34:1-34:4, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024) https://doi.org/10.4230/LIPIcs.IPEC.2024.34

Author Details

Kenneth Langedal
  • University of Bergen, Norway
Matthias Bentert
  • University of Bergen, Norway
Thorgal Blanco
  • University of Bergen, Norway
Pål Grønås Drange
  • University of Bergen, Norway

Supplementary Materials

References

  1. Kenneth Langedal. KennethLangedal/PACE2024-UiB: pace-2024, June 2024. URL: https://doi.org/10.5281/zenodo.11540761.
  2. Eugene L. Lawler. A comment on minimum feedback arc sets. IEEE Transactions on Circuit Theory, 11(2):296-297, 1964. Google Scholar
  3. Sungju Park and Sheldon B. Akers. An efficient method for finding a minimal feedback arc set in directed graphs. In 1992 IEEE International Symposium on Circuits and Systems, volume 4, pages 1863-1866. IEEE, 1992. Google Scholar
  4. Marek Piotrów. UWrMaxSat: Efficient solver for MaxSAT and pseudo-boolean problems. In 2020 IEEE 32nd International Conference on Tools with Artificial Intelligence (ICTAI), pages 132-136. IEEE, 2020. URL: https://doi.org/10.1109/ICTAI50040.2020.00031.
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