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

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

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.

Original languageEnglish
Title of host publicationProduction Research - 10th International Conference of Production Research - Americas, ICPR-Americas 2020, Revised Selected Papers
EditorsDaniel Alejandro Rossit, Fernando Tohmé, Gonzalo Mejía Delgadillo
PublisherSpringer Science and Business Media Deutschland GmbH
Pages85-96
Number of pages12
ISBN (Print)9783030763060
DOIs
StatePublished - 2021
Event10th International Conference of Production Research - Americas, ICPR-Americas 2020 - Virtual, Online
Duration: 9 Dec 202011 Dec 2020

Publication series

NameCommunications in Computer and Information Science
Volume1407 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference10th International Conference of Production Research - Americas, ICPR-Americas 2020
CityVirtual, Online
Period9/12/2011/12/20

Bibliographical note

Publisher Copyright:
© 2021, Springer Nature Switzerland AG.

Keywords

  • Flexibility factors
  • Forecast error
  • Production planning
  • Rolling horizon

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