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Computing a maximum clique in geometric superclasses of disk graphs

In the 90’s Clark, Colbourn and Johnson wrote a seminal paper where they proved that maximum clique can be solved in polynomial time in unit disk graphs. Since then, the complexity of maximum clique in intersection graphs of d-dimensional (unit) balls has been investigated. For ball graphs, the prob...

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Autor principal: Grelier, Nicolas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9568498/
https://www.ncbi.nlm.nih.gov/pubmed/36258784
http://dx.doi.org/10.1007/s10878-022-00853-2
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author Grelier, Nicolas
author_facet Grelier, Nicolas
author_sort Grelier, Nicolas
collection PubMed
description In the 90’s Clark, Colbourn and Johnson wrote a seminal paper where they proved that maximum clique can be solved in polynomial time in unit disk graphs. Since then, the complexity of maximum clique in intersection graphs of d-dimensional (unit) balls has been investigated. For ball graphs, the problem is NP-hard, as shown by Bonamy et al. (FOCS ’18). They also gave an efficient polynomial time approximation scheme (EPTAS) for disk graphs. However, the complexity of maximum clique in this setting remains unknown. In this paper, we show the existence of a polynomial time algorithm for a geometric superclass of unit disk graphs. Moreover, we give partial results toward obtaining an EPTAS for intersection graphs of convex pseudo-disks.
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spelling pubmed-95684982022-10-16 Computing a maximum clique in geometric superclasses of disk graphs Grelier, Nicolas J Comb Optim Article In the 90’s Clark, Colbourn and Johnson wrote a seminal paper where they proved that maximum clique can be solved in polynomial time in unit disk graphs. Since then, the complexity of maximum clique in intersection graphs of d-dimensional (unit) balls has been investigated. For ball graphs, the problem is NP-hard, as shown by Bonamy et al. (FOCS ’18). They also gave an efficient polynomial time approximation scheme (EPTAS) for disk graphs. However, the complexity of maximum clique in this setting remains unknown. In this paper, we show the existence of a polynomial time algorithm for a geometric superclass of unit disk graphs. Moreover, we give partial results toward obtaining an EPTAS for intersection graphs of convex pseudo-disks. Springer US 2022-03-25 2022 /pmc/articles/PMC9568498/ /pubmed/36258784 http://dx.doi.org/10.1007/s10878-022-00853-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Grelier, Nicolas
Computing a maximum clique in geometric superclasses of disk graphs
title Computing a maximum clique in geometric superclasses of disk graphs
title_full Computing a maximum clique in geometric superclasses of disk graphs
title_fullStr Computing a maximum clique in geometric superclasses of disk graphs
title_full_unstemmed Computing a maximum clique in geometric superclasses of disk graphs
title_short Computing a maximum clique in geometric superclasses of disk graphs
title_sort computing a maximum clique in geometric superclasses of disk graphs
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9568498/
https://www.ncbi.nlm.nih.gov/pubmed/36258784
http://dx.doi.org/10.1007/s10878-022-00853-2
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