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    Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10259/8433

    Título
    Grouping products for the optimization of production processes: A case in the steel manufacturing industry
    Autor
    Casado Yusta, SilviaUBU authority Orcid
    Laguna, Manuel
    Pacheco Bonrostro, JoaquínUBU authority Orcid
    Puche Regaliza, Julio CésarUBU authority Orcid
    Publicado en
    European Journal of Operational Research. 2020, V. 286, n. 1, p. 190-202
    Editorial
    Elsevier
    Fecha de publicación
    2020-10
    ISSN
    0377-2217
    DOI
    10.1016/j.ejor.2020.03.010
    Abstract
    The optimization of a production process is often based on the efficient utilization of the production facility and equipment. In particular, reducing the time to change from producing one product to another is critical to the fulfillment of demand at a minimum cost. We study the production of steel coils in the context of searching for groups of products with similar characteristics in order to create production batches that minimize the cost of fulfilling production orders originated by a known demand. We formulate the problem as mixed-integer program and develop a heuristic solution procedure. We show that a simplified version of the problem is equivalent to the clique partition problem, which in turn is equivalent to the graph-coloring problem. Computational experiments show that the heuristic procedure is effective in finding high-quality solutions to both the clique partition problem and the original grouping problem that includes additional costs.
    Palabras clave
    Metaheuristics
    Combinatorial optimization
    Manufacturing
    Materia
    Economía
    Economics
    Gestión de empresas
    Industrial management
    URI
    http://hdl.handle.net/10259/8433
    Versión del editor
    https://doi.org/10.1016/j.ejor.2020.03.010
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    Documento(s) sujeto(s) a una licencia Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 Internacional
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