Work

Demand forecasting in restaurants using machine learning and statistical analysis

Year: 2019

Type: article

Abstract: In this paper, demand forecasting in restaurants using machine learning is proposed. Many researches have been proposed on demand forecasting technology using POS data. However, in order to make demand forecasts at a real store, it is necessary to establish a store-specific demand forecasting model in consideration of various factors such as the store location, the weather, events, etc. Therefore, we constructed a demand forecasting model that functionally combines the above mentioned data using machine learning. In this paper, the demand forecasting model using machine learning and the verification result of the model using real store data is discussed.

Source: Procedia CIRP

DOI: 10.1016/j.procir.2019.02.042

Authors: Takashi Tanizaki, Tomohiro Hoshino, Takeshi Shimmura, Takeshi Takenaka

Institutions: Kindai University, Ritsumeikan University, National Institute of Advanced Industrial Science and Technology

Language: English

Topic: Forecasting Techniques and Applications

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

Open Access status: diamond

Funder: Japan Society for the Promotion of Science

Award: Study on service system design and operation method based on future forecast information