AI-BASED FOOD DEMAND PREDICTION FOR RESTAURANT

One of the biggest problems facing the food and restaurant businesses is that they have to māanage customer demand. Customer demand s unpredictable and will vary based on many factors including seasonality, trends and external influences (e.g., holidays, weather). This is a problem when restaurants miscalculate (overestimate) customer demand because then they can have a lot of food waste. In contrast, when restaurants miscalculate (underestimate) customer demand, then customers will be unhappy and there will be a loss of revenue for the restaurant. To help solve the issue associated with accurately forecasting customer food demand, the purpose of this project is to develop an artificial intelligence tool to help predict future food demand for restaurants.As part of developing a predictive model, the system will use historical sales data along with other data (i.e., key attributes such as date, day of week, holiday and previous sales) to develop customer order patterns. The identified customer order patterns will then be used to generate accurate future food demand forecasts, using several different machine learning algorithms including Linear Regression, among others.