A Production Planning MILP Optimization Model for a Manufacturing Company

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dc.coverageDOI: 10.1007/978-3-030-76307-7_7
dc.creatorCedillo-Robles, Juan Antonio
dc.creatorSmith, Neale R.
dc.creatorGonzález, Rosa Guadalupe
dc.creatorAlonso-Stocker, Julio
dc.creatorAlonso-Stocker, Joaquín
dc.creatorAskin, Ronald G.
dc.date2021
dc.date.accessioned05-01-2026 18:12
dc.date.available05-01-2026 18:12
dc.description<p>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<sup>k</sup> 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.</p>eng
dc.identifierhttps://investigadores.uandes.cl/en/publications/f3b78f6a-97ed-4107-af52-3a3a927218e4
dc.languageeng
dc.publisherSpringer Science and Business Media Deutschland GmbH
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.sourceRossit, Daniel Alejandro, Tohmé, Fernando, Mejía Delgadillo, Gonzalo (Ed.), Production Research - 10th International Conference of Production Research - Americas, ICPR-Americas 2020, Revised Selected Papers, p.85-96. Springer Science and Business Media Deutschland GmbH. [ISBN 9783030763060]
dc.subjectFlexibility factors
dc.subjectForecast error
dc.subjectProduction planning
dc.subjectRolling horizon
dc.titleA Production Planning MILP Optimization Model for a Manufacturing Companyeng
dc.typeConference contributioneng
dc.typeContribución a la conferenciaspa
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Doctorado en Ciencias de la Ingeniería (DOCI)