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Title: | Evolving reordering algorithms using an ant colony hyperheuristic approach for accelerating the convergence of the ICCG method |
Keywords: | Bandwidth reduction Profle reduction Heuristics Reordering algorithms Sparse matrices Renumbering Graph labeling Conjugate gradient method Graph algorithm Incomplete Cholesky factorization Ant colony optimization Hyperheuristic Redução da largura de banda Redução de perfil Heurística Algoritmos de reordenação Matrizes esparsas Renumeração Rotulagem de gráfico Método de gradiente conjugado Algoritmo gráfico Fatoração incompleta de Cholesky Otimização de colônia de formigas Hiperheurística |
Issue Date: | 2020 |
Publisher: | Elsevier |
Citation: | OLIVEIRA, S. L. G. de; SILVA, L. M. Evolving reordering algorithms using an ant colony hyperheuristic approach for accelerating the convergence of the ICCG method. Engineering with Computers, New York, v. 36, p. 1857-1873, 2020. DOI: 10.1007/s00366-019-00801-5. |
Abstract: | This paper proposes a novel ant colony hyperheuristic approach for reordering the rows and columns of symmetric positive defnite matrices. This ant colony hyperheuristic approach evolves heuristics for bandwidth reduction applied to instances arising from specifc application areas with the objective of generating low-cost reordering algorithms. This paper evaluates the resulting reordering algorithm in each application area against state-of-the-art reordering algorithms with the purpose of reducing the running times of the zero-fll incomplete Cholesky-preconditioned conjugate gradient method. The results obtained on a wide-ranging set of standard benchmark matrices show that the proposed approach compares favorably with state-of-the-art reordering algorithms when applied to instances arising from computational fuid dynamics, structural, and thermal problems. |
URI: | https://doi.org/10.1007/s00366-019-00801-5 http://repositorio.ufla.br/jspui/handle/1/48109 |
Appears in Collections: | DCC - Artigos publicados em periódicos |
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