Distribution planning model with multi-products in a supply chain: a case study in FMCG company

The Fast-Moving Consumer Goods (FMCG) industry, characterized by products with a short shelf life and high consumer demand, faces the challenge of effectively managing transportation costs for product distribution. In this dynamic market, where competition is severe and consumer preferences are constantly changing, the ability to optimize transportation procedures is critical for businesses looking to maintain a competitive advantage. This study introduces a mixed-integer programming approach to daily distribution requirement planning to optimize logistics costs. Utilizing real-world data from an FMCG company, the feasibility and efficacy of our model are demonstrated. The distribution network encompasses two factories, three distribution centers, and delivery across ten provinces with significant outputs. Finally, the model demonstrated that the problem was solved in an acceptable amount of time and provided a realistically optimal solution to the distribution requirement planning problem. This is the input for daily production scheduling in the factory.