Please use this identifier to cite or link to this item: http://www.repositorio.ufop.br/jspui/handle/123456789/14578
Title: SCO-Concat : a solution to a planning problem in flexible manufacturing systems using supervisory control theory and optimization techniques.
Authors: Costa, Tatiana Alves
Pena, Patrícia Nascimento
Takahashi, Ricardo Hiroshi Caldeira
Keywords: Scheduling
Metaheuristics
Issue Date: 2018
Citation: COSTA, T. A.; PENA, P. N.; TAKAHASHI, R. H. C. SCO-Concat: a solution to a planning problem in flexible manufacturing systems using supervisory control theory and optimization techniques. Journal Of Control, Automation and Electrical Systems, v. 29, p. 500-511, maio 2018. Disponível em: <https://link.springer.com/article/10.1007/s40313-018-0386-7>. Acesso em: 12 set. 2021.
Abstract: This work presents a modified version of the SCO (Supervisory Control and Optimization) methodology, proposed in Pena et al. (Inf Sci 329:491–502, 2016) to deal with planning problems in flexible manufacturing systems. Although having proved to be an alternative to deal with this class of problems, the SCO methodology is limited by the fact that it can only be applied to deal with small batches of products. Previous works show that when considering manufacturing systems of a moderate degree of complexity, this approach is only efficient to generate solutions for batches containing very few products, as for larger batches, the necessary computational time to process a solution is very high. It is obvious that, for the problems in the real world, this dimension of production is very small, which, at first, makes the application of SCO methodology quite limited. Therefore, this work proposes a complementary approach to SCO, here called SCO-Concat, developed to carry out the planning in larger batches of production. The proposed methodology was tested in a plant of moderate size, and the results obtained show that planning for batches as large as desired can be achieved in an efficient manner by SCO-Concat at a very reduced computational cost.
URI: http://www.repositorio.ufop.br/jspui/handle/123456789/14578
metadata.dc.identifier.uri2: https://link.springer.com/article/10.1007/s40313-018-0386-7
metadata.dc.identifier.doi: https://doi.org/10.1007/s40313-018-0386-7
ISSN: 2195-3899
Appears in Collections:DECSI - Artigos publicados em periódicos

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