The project involved forecasting the daily demand of lettuce in four individual fast-food restaurants over a two-week period using multiple time series forecasting models, including Holt-Winters and ARIMA, implemented in R. Additionally, the project aimed to evaluate the performance of each model to determine the most effective approach for forecasting demand at each store. The datasets contained transaction information, ingredients lists, and metadata about the restaurants. The final goal was to assist managers in making inventory replenishment decisions by providing accurate demand forecasts.

code.Rmd file contains the R code

report.html file contains the report (code + conclusions) -> In order to correctly visualize it, you can access it here: https://htmlpreview.github.io/?https://github.com/anar39/Forecasting-Project/blob/main/report.html