Metaheuristic algorithms for the bandwidth reduction of large-scale matrices

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MetadadosDescriçãoIdioma
Autor(es): dc.creatorOliveira, S. L. Gonzaga de-
Autor(es): dc.creatorCarvalho, C.-
Data de aceite: dc.date.accessioned2026-02-09T11:28:58Z-
Data de disponibilização: dc.date.available2026-02-09T11:28:58Z-
Data de envio: dc.date.issued2022-10-25-
Data de envio: dc.date.issued2022-10-25-
Data de envio: dc.date.issued2021-
Fonte completa do material: dc.identifierhttps://repositorio.ufla.br/handle/1/55343-
Fonte completa do material: dc.identifierhttps://doi.org/10.1007/s10878-021-00801-6-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/1141707-
Descrição: dc.descriptionThis paper considers the bandwidth reduction problem for large-scale sparse matrices in serial computations. A heuristic for bandwidth reduction reorders the rows and columns of a given sparse matrix. Thus, the method places entries with a nonzero value as close to the main diagonal as possible. Bandwidth optimization is a critical issue for many scientific and engineering applications. This manuscript proposes two heuristics for the bandwidth reduction of large-scale matrices. The first is a variant of the Fast Node Centroid Hill-Climbing algorithm, and the second is an algorithm based on the iterated local search metaheuristic. This paper then experimentally compares the solutions yielded by the new reordering algorithms with the bandwidth solutions delivered by state-of-the-art heuristics for the problem, including tests on large-scale problem matrices. A considerable number of results for a range of realistic test problems showed that the performance of the two new algorithms compared favorably with state-of-the-art heuristics for bandwidth reduction. Specifically, the variant of the Fast Node Centroid Hill-Climbing algorithm yielded the overall best bandwidth results.-
Idioma: dc.languageen-
Publicador: dc.publisherSpringer-
Direitos: dc.rightsrestrictAccess-
???dc.source???: dc.sourceJournal of Combinatorial Optimization-
Palavras-chave: dc.subjectBandwidth reduction-
Palavras-chave: dc.subjectHeuristics-
Palavras-chave: dc.subjectSparse matrices-
Palavras-chave: dc.subjectReordering algorithms-
Palavras-chave: dc.subjectMetaheuristics-
Palavras-chave: dc.subjectGraph algorithm-
Palavras-chave: dc.subjectIterated local search-
Palavras-chave: dc.subjectRedução da largura de banda-
Palavras-chave: dc.subjectHeurística-
Palavras-chave: dc.subjectMatrizes esparsas-
Palavras-chave: dc.subjectMetaheurísticas-
Palavras-chave: dc.subjectAlgoritmo de gráfico-
Palavras-chave: dc.subjectAlgoritmos de reordenação-
Palavras-chave: dc.subjectPesquisa local iterada-
Título: dc.titleMetaheuristic algorithms for the bandwidth reduction of large-scale matrices-
Tipo de arquivo: dc.typeArtigo-
Aparece nas coleções:Repositório Institucional da Universidade Federal de Lavras (RIUFLA)

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