A PageRank-based heuristic for the minimization of open stacks problem.

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MetadadosDescriçãoIdioma
Autor(es): dc.creatorFrinhani, Rafael de Magalhães Dias-
Autor(es): dc.creatorCarvalho, Marco Antonio Moreira de-
Autor(es): dc.creatorSoma, Nei Yoshihiro-
Data de aceite: dc.date.accessioned2025-08-21T15:55:54Z-
Data de disponibilização: dc.date.available2025-08-21T15:55:54Z-
Data de envio: dc.date.issued2019-05-17-
Data de envio: dc.date.issued2019-05-17-
Data de envio: dc.date.issued2018-
Fonte completa do material: dc.identifierhttp://www.repositorio.ufop.br/handle/123456789/11341-
Fonte completa do material: dc.identifierhttps://doi.org/10.1371/journal.pone.0203076-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/1027780-
Descrição: dc.descriptionThe minimization of open stacks problem (MOSP) aims to determine the ideal production sequence to optimize the occupation of physical space in manufacturing settings. Most of current methods for solving the MOSP were not designed to work with large instances, precluding their use in specific cases of similar modeling problems. We therefore propose a PageRank-based heuristic to solve large instances modeled in graphs. In computational experiments, both data from the literature and new datasets up to 25 times fold larger in input size than current datasets, totaling 1330 instances, were analyzed to compare the proposed heuristic with state-of-the-art methods. The results showed the competitiveness of the proposed heuristic in terms of quality, as it found optimal solutions in several cases, and in terms of shorter run times compared with the fastest available method. Furthermore, based on specific graph densities, we found that the difference in the value of solutions between methods was small, thus justifying the use of the fastest method. The proposed heuristic is scalable and is more affected by graph density than by size.-
Formato: dc.formatapplication/pdf-
Idioma: dc.languageen-
Direitos: dc.rightsaberto-
Direitos: dc.rightsThis is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Fonte: o próprio artigo-
Título: dc.titleA PageRank-based heuristic for the minimization of open stacks problem.-
Aparece nas coleções:Repositório Institucional - UFOP

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