RT dataset
T1 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.
A1 Casado Yusta, Silvia
A1 Laguna, Manuel
A1 Pacheco Bonrostro, Joaquín
A1 Puche Regaliza, Julio César
K1 Metaheuristics
K1 Combinatorial optimization
K1 Manufacturing
K1 Investigación operativa
K1 Operations research
K1 Gestión de empresas
K1 Industrial management
AB 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.
PB Universidad de Burgos
YR 2019
FD 2019
LK http://hdl.handle.net/10259/9819
UL http://hdl.handle.net/10259/9819
LA eng
NO This work was partially supported by FEDER funds and the Spanish Ministry of Economy and Competitiveness (Projects ECO2013-47129-C4-3-R and ECO2016-76567-C4-2-R), the Regional Government of Castilla y León, Spain (Project BU329U14 and BU071G19), and the Regional Government of Castilla y León and FEDER funds (Project BU062U16).
DS Repositorio Institucional de la Universidad de Burgos
RD 22-dic-2024