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dc.contributor.authorComellas Padró, Francesc de Paula
dc.contributor.authorDíaz López, Jordi
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Matemàtica Aplicada IV
dc.date.accessioned2007-05-25T18:53:28Z
dc.date.available2007-05-25T18:53:28Z
dc.date.issued2007-05-24
dc.identifier.urihttp://hdl.handle.net/2117/1037
dc.description.abstractIn 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.
dc.format.extent10
dc.language.isoeng
dc.rightsAttribution-NonCommercial-NoDerivs 2.5 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/2.5/es/
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística
dc.subject.lcshCombinatorics
dc.subject.othergraphs
dc.subject.otherspectrum
dc.titleSpectral reconstruction of networks using combinatorial optimization algorithms
dc.typeArticle
dc.subject.lemacCombinacions (Matemàtica)
dc.contributor.groupUniversitat Politècnica de Catalunya. COMBGRAPH - Combinatòria, Teoria de Grafs i Aplicacions
dc.subject.amsClassificació AMS::05 Combinatorics
dc.rights.accessOpen Access
dc.relation.projectidcttTEC2005-03575


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Except where otherwise noted, content on this work is licensed under a Creative Commons license: Attribution-NonCommercial-NoDerivs 2.5 Spain