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    Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10259/9819

    Título
    Dataset of the paper “Grouping products for the optimization of production processes: A case in the steel manufacturing industry”. European Journal of Operational Research, 286(1), 190-202
    Autor
    Casado Yusta, SilviaAutoridad UBU Orcid
    Laguna, Manuel
    Pacheco Bonrostro, JoaquínAutoridad UBU Orcid
    Puche Regaliza, Julio CésarAutoridad UBU Orcid
    Editorial
    Universidad de Burgos
    Fecha de publicación
    2019
    DOI
    10.71486/fna8-4y35
    Resumo
    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
    Investigación operativa
    Operations research
    Gestión de empresas
    Industrial management
    URI
    http://hdl.handle.net/10259/9819
    Referenciado en
    http://hdl.handle.net/10259/8433
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