Plate Waste Forecasting Using the Monte Carlo Method for Effective Decision Making in Latvian Schools
Sergejs Kodors; Anda Zvaigzne; Lienite Litavniece; Jelena Lonska; Inese Silicka; Inta Kotane; Juta Deksne
Food waste is a global problem, which becomes apparent at various stages of the food supply chain. The present research study focuses on the optimization of food consumption in schools and effective food management through data-driven decision making within the trends: zero food waste and digital transformation. The paper presents a plate waste forecasting system based on mathematical modeling and simulation using the Monte Carlo method, which showed an RMSE equal to ±:3% and a MAPE of 10.15%. The solution based on the simulator provides a possibility to better understand the relationship between the parameters investigated through data visualization and apply this knowledge to train managers to make decisions that are more effective. The developed system has multi-disciplinary application: forecasting, education and decision making targeted to reduce food waste and improve public health and food management in schools.
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