Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Chen, Li-Hsuan, Hung, Ling-Ju, Lotze, Henri, Rossmanith, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
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
_version_ 1783539636562296832
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
work_keys_str_mv AT chenlihsuan furtherresultsononlinenodeandedgedeletionproblemswithadvice
AT hunglingju furtherresultsononlinenodeandedgedeletionproblemswithadvice
AT lotzehenri furtherresultsononlinenodeandedgedeletionproblemswithadvice
AT rossmanithpeter furtherresultsononlinenodeandedgedeletionproblemswithadvice