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Analysis of Flexibility for the Integrated lot sizing and Blending Problem

Grant number: 22/15888-6
Support Opportunities:Scholarships in Brazil - Scientific Initiation
Effective date (Start): March 01, 2023
Effective date (End): February 29, 2024
Field of knowledge:Engineering - Production Engineering - Operational Research
Principal Investigator:Diego Jacinto Fiorotto
Grantee:Vinícius Consentino Muniz
Host Institution: Faculdade de Ciências Aplicadas (FCA). Universidade Estadual de Campinas (UNICAMP). Limeira , SP, Brazil


The standard blending problem consists of combining ingredients to produce a final product with a given demand, while satisfying specific criteria with respect to the global blend and minimizing the total cost. This problem has been widely studied in a single period setting. However, the problem becomes more complex when we take into account a longer time frame. In such a case, demand for the final product occurs in several time periods, and both the final product and the ingredients can be held in stock. In this case, we consider the sizing problem of a final product that can be produced by blending different ingredients. For this problem, the Bill-Of-Material indicates which ingredients are used and in which proportion. With the natural evolution of the industrial decision making process due, among others factors, the strong competition imposed by the globalized market, different strategies have been used to improve the decisions, making them more complex. Among these strategies, recently it has appeared studies which consider that some data, although deterministic, have certain flexibility, making the problem similar to what happens in practice. In this project we intend to study the Bill-Of-Material flexibility to the integrated lot sizing and blending problem. The idea is that in some productive processes there is some flexibility with respect to the proportion imposed for each of the ingredients, where it can vary between a minimum and maximum instead of being fixed, this provides flexibility in the production planning process.

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