Spectral reconstruction of networks using combinatorial optimization algorithms

In this paper we study the reconstruction of a network topology from the eigenvalues of its Laplacian matrix. We introduce a new simple cost function and consider three combinatorial optimization methods - simulated annealing, tabu search, and multiagent optimization (ants)- while comparing their pe...

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Detalhes bibliográficos
Autores: Comellas Padró, Francesc de Paula|||0000-0003-4523-0240, Díaz López, Jordi
Tipo de documento: artigo
Data de publicação:2007
País:España
Recursos:Universitat Politècnica de Catalunya (UPC)
Repositório:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglês
OAI Identifier:oai:upcommons.upc.edu:2117/1037
Acesso em linha:https://hdl.handle.net/2117/1037
Access Level:Acceso aberto
Palavra-chave:Combinatorics
graphs
spectrum
Combinacions (Matemàtica)
Classificació AMS::05 Combinatorics
Àrees temàtiques de la UPC::Matemàtiques i estadística
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spelling Spectral reconstruction of networks using combinatorial optimization algorithmsComellas Padró, Francesc de Paula|||0000-0003-4523-0240Díaz López, JordiCombinatoricsgraphsspectrumCombinacions (Matemàtica)Classificació AMS::05 CombinatoricsÀrees temàtiques de la UPC::Matemàtiques i estadísticaIn this paper we study the reconstruction of a network topology from the eigenvalues of its Laplacian matrix. We introduce a new simple cost function and consider three combinatorial optimization methods - simulated annealing, tabu search, and multiagent optimization (ants)- while comparing their performance when reconstructing different categories of networks --random, regular, small-world, scale-free and clustered-- from their eigenvalues. We show that tabu search provides more accurate reconstructions than the other methods, while all the algorithms considered allow an exact reconstruction of small networks and lead to good approximations in the case of networks with larger orders.20072007-05-2420072007-05-25journal articlehttp://purl.org/coar/resource_type/c_6501NAhttp://purl.org/coar/version/c_be7fb7dd8ff6fe43info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/1037reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution-NonCommercial-NoDerivs 2.5 Spainhttp://creativecommons.org/licenses/by-nc-nd/2.5/es/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/10372026-05-27T15:37:01Z
dc.title.none.fl_str_mv Spectral reconstruction of networks using combinatorial optimization algorithms
title Spectral reconstruction of networks using combinatorial optimization algorithms
spellingShingle Spectral reconstruction of networks using combinatorial optimization algorithms
Comellas Padró, Francesc de Paula|||0000-0003-4523-0240
Combinatorics
graphs
spectrum
Combinacions (Matemàtica)
Classificació AMS::05 Combinatorics
Àrees temàtiques de la UPC::Matemàtiques i estadística
title_short Spectral reconstruction of networks using combinatorial optimization algorithms
title_full Spectral reconstruction of networks using combinatorial optimization algorithms
title_fullStr Spectral reconstruction of networks using combinatorial optimization algorithms
title_full_unstemmed Spectral reconstruction of networks using combinatorial optimization algorithms
title_sort Spectral reconstruction of networks using combinatorial optimization algorithms
dc.creator.none.fl_str_mv Comellas Padró, Francesc de Paula|||0000-0003-4523-0240
Díaz López, Jordi
author Comellas Padró, Francesc de Paula|||0000-0003-4523-0240
author_facet Comellas Padró, Francesc de Paula|||0000-0003-4523-0240
Díaz López, Jordi
author_role author
author2 Díaz López, Jordi
author2_role author
dc.subject.none.fl_str_mv Combinatorics
graphs
spectrum
Combinacions (Matemàtica)
Classificació AMS::05 Combinatorics
Àrees temàtiques de la UPC::Matemàtiques i estadística
topic Combinatorics
graphs
spectrum
Combinacions (Matemàtica)
Classificació AMS::05 Combinatorics
Àrees temàtiques de la UPC::Matemàtiques i estadística
description In this paper we study the reconstruction of a network topology from the eigenvalues of its Laplacian matrix. We introduce a new simple cost function and consider three combinatorial optimization methods - simulated annealing, tabu search, and multiagent optimization (ants)- while comparing their performance when reconstructing different categories of networks --random, regular, small-world, scale-free and clustered-- from their eigenvalues. We show that tabu search provides more accurate reconstructions than the other methods, while all the algorithms considered allow an exact reconstruction of small networks and lead to good approximations in the case of networks with larger orders.
publishDate 2007
dc.date.none.fl_str_mv 2007
2007-05-24
2007
2007-05-25
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
NA
http://purl.org/coar/version/c_be7fb7dd8ff6fe43
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/1037
url https://hdl.handle.net/2117/1037
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivs 2.5 Spain
http://creativecommons.org/licenses/by-nc-nd/2.5/es/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivs 2.5 Spain
http://creativecommons.org/licenses/by-nc-nd/2.5/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,198674

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