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Further Results on Online Node- and Edge-Deletion Problems with Advice
In online edge- and node-deletion problems the input arrives node by node and an algorithm has to delete nodes or edges in order to keep the input graph in a given graph class at all times. We consider graph classes that can be characterized by forbidden sets of induced subgraphs and analyze the adv...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7254923/ http://dx.doi.org/10.1007/978-3-030-48966-3_11 |
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author | Chen, Li-Hsuan Hung, Ling-Ju Lotze, Henri Rossmanith, Peter |
author_facet | Chen, Li-Hsuan Hung, Ling-Ju Lotze, Henri Rossmanith, Peter |
author_sort | Chen, Li-Hsuan |
collection | PubMed |
description | In online edge- and node-deletion problems the input arrives node by node and an algorithm has to delete nodes or edges in order to keep the input graph in a given graph class at all times. We consider graph classes that can be characterized by forbidden sets of induced subgraphs and analyze the advice complexity of getting an optimal solution. We give almost tight lower and upper bounds for the [Image: see text] , where there is one forbidden induced subgraph that may or may not be disconnected and tight bounds on the [Image: see text] , where we have an arbitrary number of forbidden connected graphs. For the latter result we present an algorithm that computes the advice complexity directly from [Formula: see text]. For the [Image: see text] the advice complexity is basically an easy function of the size of the biggest component in H. |
format | Online Article Text |
id | pubmed-7254923 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
record_format | MEDLINE/PubMed |
spelling | pubmed-72549232020-05-28 Further Results on Online Node- and Edge-Deletion Problems with Advice Chen, Li-Hsuan Hung, Ling-Ju Lotze, Henri Rossmanith, Peter Combinatorial Algorithms Article In online edge- and node-deletion problems the input arrives node by node and an algorithm has to delete nodes or edges in order to keep the input graph in a given graph class at all times. We consider graph classes that can be characterized by forbidden sets of induced subgraphs and analyze the advice complexity of getting an optimal solution. We give almost tight lower and upper bounds for the [Image: see text] , where there is one forbidden induced subgraph that may or may not be disconnected and tight bounds on the [Image: see text] , where we have an arbitrary number of forbidden connected graphs. For the latter result we present an algorithm that computes the advice complexity directly from [Formula: see text]. For the [Image: see text] the advice complexity is basically an easy function of the size of the biggest component in H. 2020-04-30 /pmc/articles/PMC7254923/ http://dx.doi.org/10.1007/978-3-030-48966-3_11 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Chen, Li-Hsuan Hung, Ling-Ju Lotze, Henri Rossmanith, Peter Further Results on Online Node- and Edge-Deletion Problems with Advice |
title | Further Results on Online Node- and Edge-Deletion Problems with Advice |
title_full | Further Results on Online Node- and Edge-Deletion Problems with Advice |
title_fullStr | Further Results on Online Node- and Edge-Deletion Problems with Advice |
title_full_unstemmed | Further Results on Online Node- and Edge-Deletion Problems with Advice |
title_short | Further Results on Online Node- and Edge-Deletion Problems with Advice |
title_sort | further results on online node- and edge-deletion problems with advice |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7254923/ http://dx.doi.org/10.1007/978-3-030-48966-3_11 |
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