A mixed-integer linear programming model for the cutting stock problem in the steel industry

A mixed-integer linear programming (MILP) model is proposed for solving a one dimension cutting stock problem (1D-CSP) in the steel industry. A case study of a metallurgical company is presented and the objective is to minimize waste in the cutting process of steel bars, considering inventory constr...

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Autores:
Morillo-Torres, Daniel
Torres Baena, Mauricio
Escobar, John Wilmer
Romero-Conrado, Alfonso R.
Romero-Conrado, Alfonso R.
Gustavo, Gatica
Tipo de recurso:
Part of book
Fecha de publicación:
2021
Institución:
Corporación Universidad de la Costa
Repositorio:
REDICUC - Repositorio CUC
Idioma:
eng
OAI Identifier:
oai:repositorio.cuc.edu.co:11323/9356
Acceso en línea:
https://hdl.handle.net/11323/9356
https://doi.org/10.1007/978-3-030-86702-7_27
https://repositorio.cuc.edu.co/
Palabra clave:
Cutting stock problem
Mixed-integer linear programming
Steel bars
Industrial application
Rights
openAccess
License
Atribución-NoComercial-CompartirIgual 4.0 Internacional (CC BY-NC-SA 4.0)
Description
Summary:A mixed-integer linear programming (MILP) model is proposed for solving a one dimension cutting stock problem (1D-CSP) in the steel industry. A case study of a metallurgical company is presented and the objective is to minimize waste in the cutting process of steel bars, considering inventory constraints and the potential use of the resulting leftovers. The computational results showed that an optimal solution was always found with an average improvement in waste reduction of 80%. There was no significant difference when comparing results between the complete model and the model without inventory constraints.