License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.SoCG.2020.84
URN: urn:nbn:de:0030-drops-122423
URL: https://drops.dagstuhl.de/opus/volltexte/2020/12242/
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Moalic, Laurent ; Schmitt, Dominique ; Lepagnot, Julien ; Kritter, Julien

Computing Low-Cost Convex Partitions for Planar Point Sets Based on a Memetic Approach (CG Challenge)

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LIPIcs-SoCG-2020-84.pdf (1 MB)


Abstract

We present a memetic approach designed to tackle the 2020 Computational Geometry Challenge on the Minimum Convex Partition problem. It is based on a simple local search algorithm hybridized with a genetic approach. The population is brought down to its smallest possible size - only 2 individuals - for a very simple implementation. This algorithm was applied to all the instances, without any specific parameterization or adaptation.

BibTeX - Entry

@InProceedings{moalic_et_al:LIPIcs:2020:12242,
  author =	{Laurent Moalic and Dominique Schmitt and Julien Lepagnot and Julien Kritter},
  title =	{{Computing Low-Cost Convex Partitions for Planar Point Sets Based on a Memetic Approach (CG Challenge)}},
  booktitle =	{36th International Symposium on Computational Geometry (SoCG 2020)},
  pages =	{84:1--84:9},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-143-6},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{164},
  editor =	{Sergio Cabello and Danny Z. Chen},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2020/12242},
  URN =		{urn:nbn:de:0030-drops-122423},
  doi =		{10.4230/LIPIcs.SoCG.2020.84},
  annote =	{Keywords: metaheuristics, memetic algorithms, convex partition optimization}
}

Keywords: metaheuristics, memetic algorithms, convex partition optimization
Collection: 36th International Symposium on Computational Geometry (SoCG 2020)
Issue Date: 2020
Date of publication: 08.06.2020


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