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

doi:10.1007/978-3-030-76307-7_7

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

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

2 Scopus citations

Abstract

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 2^k 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.

Original language	English
Title of host publication	Production Research - 10th International Conference of Production Research - Americas, ICPR-Americas 2020, Revised Selected Papers
Editors	Daniel Alejandro Rossit, Fernando Tohmé, Gonzalo Mejía Delgadillo
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	85-96
Number of pages	12
ISBN (Print)	9783030763060
DOIs	https://doi.org/10.1007/978-3-030-76307-7_7
State	Published - 2021
Event	10th International Conference of Production Research - Americas, ICPR-Americas 2020 - Virtual, Online Duration: 9 Dec 2020 → 11 Dec 2020

Publication series

Name	Communications in Computer and Information Science
Volume	1407 CCIS
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	10th International Conference of Production Research - Americas, ICPR-Americas 2020
City	Virtual, Online
Period	9/12/20 → 11/12/20

Bibliographical note

Publisher Copyright:
© 2021, Springer Nature Switzerland AG.

Keywords

Flexibility factors
Forecast error
Production planning
Rolling horizon

Access to Document

10.1007/978-3-030-76307-7_7

Cite this

Cedillo-Robles, J. A., Smith, N. R., González, R. G., Alonso-Stocker, J., Alonso-Stocker, J., & Askin, R. G. (2021). A Production Planning MILP Optimization Model for a Manufacturing Company. In D. A. Rossit, F. Tohmé, & G. Mejía Delgadillo (Eds.), Production Research - 10th International Conference of Production Research - Americas, ICPR-Americas 2020, Revised Selected Papers (pp. 85-96). (Communications in Computer and Information Science; Vol. 1407 CCIS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-76307-7_7

Cedillo-Robles, Juan Antonio ; Smith, Neale R. ; González, Rosa Guadalupe et al. / A Production Planning MILP Optimization Model for a Manufacturing Company. Production Research - 10th International Conference of Production Research - Americas, ICPR-Americas 2020, Revised Selected Papers. editor / Daniel Alejandro Rossit ; Fernando Tohmé ; Gonzalo Mejía Delgadillo. Springer Science and Business Media Deutschland GmbH, 2021. pp. 85-96 (Communications in Computer and Information Science).

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abstract = "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.",

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Cedillo-Robles, JA, Smith, NR, González, RG, Alonso-Stocker, J, Alonso-Stocker, J & Askin, RG 2021, A Production Planning MILP Optimization Model for a Manufacturing Company. in DA Rossit, F Tohmé & G Mejía Delgadillo (eds), Production Research - 10th International Conference of Production Research - Americas, ICPR-Americas 2020, Revised Selected Papers. Communications in Computer and Information Science, vol. 1407 CCIS, Springer Science and Business Media Deutschland GmbH, pp. 85-96, 10th International Conference of Production Research - Americas, ICPR-Americas 2020, Virtual, Online, 9/12/20. https://doi.org/10.1007/978-3-030-76307-7_7

A Production Planning MILP Optimization Model for a Manufacturing Company. / Cedillo-Robles, Juan Antonio; Smith, Neale R.; González, Rosa Guadalupe et al.
Production Research - 10th International Conference of Production Research - Americas, ICPR-Americas 2020, Revised Selected Papers. ed. / Daniel Alejandro Rossit; Fernando Tohmé; Gonzalo Mejía Delgadillo. Springer Science and Business Media Deutschland GmbH, 2021. p. 85-96 (Communications in Computer and Information Science; Vol. 1407 CCIS).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

TY - CHAP

T1 - A Production Planning MILP Optimization Model for a Manufacturing Company

AU - Cedillo-Robles, Juan Antonio

AU - Smith, Neale R.

AU - González, Rosa Guadalupe

AU - Alonso-Stocker, Julio

AU - Alonso-Stocker, Joaquín

AU - Askin, Ronald G.

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AB - 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.

KW - Flexibility factors

KW - Forecast error

KW - Production planning

KW - Rolling horizon

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SN - 9783030763060

T3 - Communications in Computer and Information Science

SP - 85

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BT - Production Research - 10th International Conference of Production Research - Americas, ICPR-Americas 2020, Revised Selected Papers

A2 - Rossit, Daniel Alejandro

A2 - Tohmé, Fernando

A2 - Mejía Delgadillo, Gonzalo

PB - Springer Science and Business Media Deutschland GmbH

T2 - 10th International Conference of Production Research - Americas, ICPR-Americas 2020

Y2 - 9 December 2020 through 11 December 2020

ER -

Cedillo-Robles JA, Smith NR, González RG, Alonso-Stocker J, Alonso-Stocker J, Askin RG. A Production Planning MILP Optimization Model for a Manufacturing Company. In Rossit DA, Tohmé F, Mejía Delgadillo G, editors, Production Research - 10th International Conference of Production Research - Americas, ICPR-Americas 2020, Revised Selected Papers. Springer Science and Business Media Deutschland GmbH. 2021. p. 85-96. (Communications in Computer and Information Science). doi: 10.1007/978-3-030-76307-7_7

A Production Planning MILP Optimization Model for a Manufacturing Company

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Keywords

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