License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.SoCG.2022.74
URN: urn:nbn:de:0030-drops-160829
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2022/16082/
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Schidler, André

SAT-Based Local Search for Plane Subgraph Partitions (CG Challenge)

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LIPIcs-SoCG-2022-74.pdf (4 MB)


Abstract

The Partition into Plane Subgraphs Problem (PPS) asks to partition the edges of a geometric graph with straight line segments into as few classes as possible, such that the line segments within a class do not cross. We discuss our approach GC-SLIM: a local search method that views PPS as a graph coloring problem and tackles it with a new and unique combination of propositional satisfiability (SAT) and tabu search, achieving the fourth place in the 2022 CG:SHOP Challenge.

BibTeX - Entry

@InProceedings{schidler:LIPIcs.SoCG.2022.74,
  author =	{Schidler, Andr\'{e}},
  title =	{{SAT-Based Local Search for Plane Subgraph Partitions}},
  booktitle =	{38th International Symposium on Computational Geometry (SoCG 2022)},
  pages =	{74:1--74:8},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-227-3},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{224},
  editor =	{Goaoc, Xavier and Kerber, Michael},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2022/16082},
  URN =		{urn:nbn:de:0030-drops-160829},
  doi =		{10.4230/LIPIcs.SoCG.2022.74},
  annote =	{Keywords: graph coloring, plane subgraphs, SAT, logic, SLIM, local improvement, large neighborhood search}
}

Keywords: graph coloring, plane subgraphs, SAT, logic, SLIM, local improvement, large neighborhood search
Collection: 38th International Symposium on Computational Geometry (SoCG 2022)
Issue Date: 2022
Date of publication: 01.06.2022
Supplementary Material: Software (Source Code): https://github.com/ASchidler/coloring archived at: https://archive.softwareheritage.org/swh:1:dir:2b7057f17495a9a12cf7de4f857037c9ab0d6654
Dataset (Results): https://doi.org/10.5281/zenodo.6352601


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