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
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
Resumen
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
Versión del editor
Aparece en las colecciones
Documento(s) sujeto(s) a una licencia Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 Internacional