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: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2020/12242/
Moalic, Laurent ;
Schmitt, Dominique ;
Lepagnot, Julien ;
Kritter, Julien
Computing Low-Cost Convex Partitions for Planar Point Sets Based on a Memetic Approach (CG Challenge)
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}
}
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Keywords: |
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metaheuristics, memetic algorithms, convex partition optimization |
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Collection: |
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36th International Symposium on Computational Geometry (SoCG 2020) |
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Issue Date: |
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2020 |
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Date of publication: |
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08.06.2020 |
