A Production Planning MILP Optimization Model for a Manufacturing Company

Juan Antonio Cedillo-Robles*, Neale R. Smith, Rosa Guadalupe González, Julio Alonso-Stocker, Joaquín Alonso-Stocker, Ronald G. Askin

*Autor correspondiente de este trabajo

Resultado de la investigación: Capítulo del libro/informe/acta de congresoCapítulorevisión exhaustiva

Resumen

This paper proposes a mixed-integer linear programming (MILP) model that is implemented based on a rolling horizon scheme to solve an aggregate production planning decision problem of a manufacturing company that produces snacks in Monterrey, Mexico. The demand of the company is characterized by trends and seasonality. The proposed solution is evaluated by means of computational experiments to determine the relation between demand uncertainty and flexibility of a production system. A 2k factorial experimental design and a multivariate regression were performed. Results show forecast bias and length of frozen period in the rolling horizon have a strong effect on total profit. The safety stock level was also found to be a significant factor, depending on the level of bias.

Idioma originalInglés
Título de la publicación alojadaProduction Research - 10th International Conference of Production Research - Americas, ICPR-Americas 2020, Revised Selected Papers
EditoresDaniel Alejandro Rossit, Fernando Tohmé, Gonzalo Mejía Delgadillo
EditorialSpringer Science and Business Media Deutschland GmbH
Páginas85-96
Número de páginas12
ISBN (versión impresa)9783030763060
DOI
EstadoPublicada - 2021
Evento10th International Conference of Production Research - Americas, ICPR-Americas 2020 - Virtual, Online
Duración: 9 dic. 202011 dic. 2020

Serie de la publicación

NombreCommunications in Computer and Information Science
Volumen1407 CCIS
ISSN (versión impresa)1865-0929
ISSN (versión digital)1865-0937

Conferencia

Conferencia10th International Conference of Production Research - Americas, ICPR-Americas 2020
CiudadVirtual, Online
Período9/12/2011/12/20

Nota bibliográfica

Publisher Copyright:
© 2021, Springer Nature Switzerland AG.

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