Modelo de Programação Linear para a Seleção de Fornecedores de Cana-de-Açúcar com Base no ATR

Abstract

The sugarcane industry plays a crucial role in the Brazilian economy, contributing significantly to the national GDP and generating direct and indirect employment opportunities. The selection of sugarcane suppliers is a critical aspect for the economic viability of sugar mills. However, this choice can be complex, involving multiple criteria and constraints.In this context, operations research emerges as an essential tool to aid decision-making regarding supplier selection. Through mathematical models and algorithms, operations research can determine the optimal combination of suppliers based on objective criteria, with TRS (Total Recoverable Sugars) being one of the most relevant indicators. Despite the importance of operations research and the ATR criterion in supplier selection, there is a research gap in evaluating the application of this methodology in supply chain management within the sugarcane industry. This thesis aims to contribute to the improvement of supply chain management in the sugarcane industry by evaluating the application of operations research in supplier selection based on the TRS criterion. A literature review on operations research in the sugar-alcohol industry was conducted, and data was collected from a specific sugar mill.By constructing a linear programming model using the OpenSolver software, the results obtained with the proposed model were analyzed and compared to the current situation of the sugar mill. The results demonstrated a significant reduction in freight costs and supplier payments, resulting in substantial savings. These findings highlight the effectiveness of the proposed model, showcasing the benefits that can be achieved through the application of operations research in the selection of sugarcane suppliers based on the TRS criterion. Overall, this study contributes to the enhancement of supply chain management in the sugarcane industry, providing valuable insights for decision-making in supplier selection and increasing efficiency, competitiveness, and sustainability within the sector.