Probabilistic Analysis of Meat Distribution Logistics: Application of Monte Carlo Simulation

Gustavo Alves de Melo, Luiz Gonzaga de Castro Júnior, Maria Gabriela Mendonça Peixoto (), Samuel Borges Barbosa, André Luiz Marques Serrano, Caroline Cambraia Furtado Campos, Matheus Vanzela and Ana Paula Dalmagro Delai
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Gustavo Alves de Melo: Institute of Exact Sciences and Technology, Federal University of Viçosa, Rio Paranaíba 38810-000, Brazil
Luiz Gonzaga de Castro Júnior: Department of Agroindustrial Management, Federal University of Lavras, Lavras 37203-202, Brazil
Maria Gabriela Mendonça Peixoto: Department of Production Engineering, University of Brasilia, Federal District, Brasília 70910-900, Brazil
Samuel Borges Barbosa: Institute of Exact Sciences and Technology, Federal University of Viçosa, Rio Paranaíba 38810-000, Brazil
André Luiz Marques Serrano: Department of Production Engineering, University of Brasilia, Federal District, Brasília 70910-900, Brazil
Caroline Cambraia Furtado Campos: Department of Agroindustrial Management, Federal University of Lavras, Lavras 37203-202, Brazil
Matheus Vanzela: Department of mathematics, Federal Institute of South Mato Grosso, Nova Andradina 79750-000, Brazil
Ana Paula Dalmagro Delai: Faculty of Agrarian Sciences, Federal University of Grande Dourados, Dourados 79825-070, Brazil

Logistics, 2025, vol. 9, issue 4, 1-26

Abstract: Background : The food sector plays a critical role in promoting population well-being and contributes significantly to economic, social, and environmental development. However, inefficiencies in distribution logistics often result in elevated operational costs, potentially compromising the viability of enterprises in this sector. This study focuses on evaluating the economic feasibility of a fresh beef and pork distribution center in the southern region of Minas Gerais, Brazil. Methods : A case study methodology with a quantitative approach was adopted. Methodological triangulation was applied by combining a traditional Economic Feasibility Analysis (EFA) with a Monte Carlo Simulation to incorporate uncertainty in key input variables. This approach enabled a comprehensive assessment of project viability under both deterministic and probabilistic conditions. Results : The results indicated that distribution price per kilogram, market share, population growth, and per capita meat consumption had a positive correlation with profitability. The economic analysis confirmed the viability of the proposed distribution center, with high expected profitability and a short payback period. The Monte Carlo Simulation revealed that market share, unit price, and consumption levels are the most influential drivers of financial performance, while logistics costs represent the main limiting factor. Conclusions : This study provides a robust, data-driven framework for investment decision-making in food logistics infrastructure. It demonstrates the value of integrating deterministic and probabilistic analyses to improve risk management and strategic planning in the food distribution sector.

Keywords: simulation; distribution logistics; meat (search for similar items in EconPapers)
JEL-codes: L8 L80 L81 L86 L87 L9 L90 L91 L92 L93 L98 L99 M1 M10 M11 M16 M19 R4 R40 R41 R49 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jlogis:v:9:y:2025:i:4:p:166-:d:1801285

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