Growing neural gas as a memory mechanism of a heuristic to solve a community detection problem in networks

dc.contributor.authorSantos, Camila Pereira [UNIFESP]
dc.contributor.authorNascimento, Maria C. V. [UNIFESP]
dc.date.accessioned2019-01-21T10:29:48Z
dc.date.available2019-01-21T10:29:48Z
dc.date.issued2016
dc.description.abstractIterative heuristics are commonly used to address combinatorial optimization problems. However, to meet both robustness and efficiency with these methods when their iterations are independent, it is necessary to consider a high number of iterations or to include local search-based strategies in them. Both approaches are very time-consuming and, consequently, not efficient for medium and large-scale instances of combinatorial optimization problems. In particular, the community detection problem in networks is well-known due to the instances with hundreds to thousands of vertices. In the literature, the heuristics to detect communities in networks that use a local search are those that achieve the partitions with the best solution values. Nevertheless, they are not suitable to tackle medium to large scale networks. This paper presents an adaptive heuristic, named GNGClus, that uses the neural network Growing Neural Gas to play the role of memory mechanism. The computational experiment with LFR networks indicates that the proposed strategy significantly outperformed the same solution method with no memory mechanism. In addition, GNGClus was very competitive with a version of the heuristic that employs an elite set of solutions to guide the solution search. (C) 2016 The Authors. Published by Elsevier B.V.en
dc.description.affiliationInstituto de Ciência e Tecnologia, Universidade Federal de São Paulo (UNIFESP) Av. Cesare M. G. Lattes, 1201, Eugênio de Mello, São José dos Campos-SP, CEP: 12247-014, Brasil
dc.description.affiliationUnifespInstituto de Ciência e Tecnologia, Universidade Federal de São Paulo (UNIFESP) Av. Cesare M. G. Lattes, 1201, Eugênio de Mello, São José dos Campos-SP, CEP: 12247-014, Brasil
dc.description.sourceWeb of Science
dc.format.extent485-494
dc.identifierhttps://doi.org/10.1016/j.procs.2016.08.110
dc.identifier.citationProcedia Computer Science. Amsterdam, v. 96, p. 485-494, 2016.
dc.identifier.doi10.1016/j.procs.2016.08.110
dc.identifier.fileWOS000383252400052.pdf
dc.identifier.issn1877-0509
dc.identifier.urihttp://repositorio.unifesp.br/handle/11600/49398
dc.identifier.wosWOS:000383252400052
dc.language.isoeng
dc.publisherFunpec-Editora
dc.relation.ispartofKnowledge-Based And Intelligent Information & Engineering Systems: Proceedings Of The 20th International Conference Kes-2016
dc.rightsAcesso aberto
dc.subjectGrowing Neural Gasen
dc.subjectCommunity Detection In Networksen
dc.subjectHeuristic Methodsen
dc.titleGrowing neural gas as a memory mechanism of a heuristic to solve a community detection problem in networksen
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