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Mathematical Problems in Engineering
Volume 2017, Article ID 6754970, 18 pages
Research Article

Alternative Mathematical Models and Solution Approaches for Lot-Sizing and Scheduling Problems in the Brewery Industry: Analyzing Two Different Situations

1Departamento de Engenharia de Produção, Universidade Federal de São Carlos, Via Washington Luiz, km. 235, 13565-905 São Carlos, SP, Brazil
2Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo, Av. Trabalhador São-Carlense 400, 13560-970 São Carlos, SP, Brazil
3INESC-TEC e Faculdade de Engenharia, Universidade do Porto, Rua Dr. Roberto Frias s/n, Porto 4200-465, Portugal

Correspondence should be addressed to Maristela O. Santos; rb.psu.cmci@iram

Received 24 January 2017; Accepted 7 June 2017; Published 10 August 2017

Academic Editor: Gen Q. Xu

Copyright © 2017 Tamara A. Baldo et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This research proposes new approaches to deal with the production planning and scheduling problem in brewery facilities. Two real situations found in factories are addressed, which differ by considering (or not) the setup operations in tanks that provide liquid for bottling lines. Depending on the technology involved in the production process, the number of tank swaps is relevant (Case A) or it can be neglected (Case B). For both scenarios, new MIP (Mixed Integer Programming) formulations and heuristic solution methods based on these formulations are proposed. In order to evaluate the approach for Case A, we compare the results of a previous study with the results obtained in this paper. For the solution methods and the result analysis of Case B, we propose adaptations of Case A approaches yielding an alternative MIP formulation to represent it. Therefore, the main contributions of this article are twofold: (i) to propose alternative MIP models and solution methods for the problem in Case A, providing better results than previously reported, and (ii) to propose new MIP models and solution methods for Case B, analyzing and comparing the results and benefits for Case B considering the technology investment required.