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Título : Heuristic methods to consecutive block minimization.
Autor : Soares, Leonardo Cabral da Rocha
Reinsma, Jordi Alves
Nascimento, Luis H. L.
Carvalho, Marco Antonio Moreira de
Palabras clave : Combinatorial problems
Metaheuristic
Iterated local search
Exact algorithms
Fecha de publicación : 2020
Citación : SOARES, L. C. da R. et al. Heuristic methods to consecutive block minimization. Computers and Operations Research, v. 120, artigo 104948, 2020. Disponível em: <https://www.sciencedirect.com/science/article/abs/pii/S0305054820300654>. Acesso em: 25 ago. 2021.
Resumen : Many combinatorial problems addressed in the literature are modeled using binary matrices. It is often of interest to verify whether these matrices hold the consecutive ones property (C1P), which implies that there exists a permutation of the columns of the matrix such that all nonzero elements can be placed contiguously, forming a unique 1-block in every row. The minimization of the number of 1-blocks is approached by a well-known problem in the literature called consecutive block minimization (CBM), an N P-hard problem. In this study, we propose a graph representation, a heuristic based on a classical algorithm in graph theory, the implementation of a metaheuristic for solving the CBM and the application of an exact method based on a reduction of the CBM to a particular version of the well-known traveling salesman problem. Computational experiments demonstrate that the proposed metaheuristic implementation is competitive, as it matches or improves the best known solution values for all benchmark instances available in the literature, except for a single instance. The proposed exact method reports, for the first time, optimal solutions for these benchmark instances. Consequently, the proposed methods outperform previous methods and become the new state-of-the-art for solving the CBM.
URI : http://www.repositorio.ufop.br/jspui/handle/123456789/14446
metadata.dc.identifier.uri2: https://www.sciencedirect.com/science/article/abs/pii/S0305054820300654
metadata.dc.identifier.doi: https://doi.org/10.1016/j.cor.2020.104948
ISSN : 0305-0548
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