Seat Allocation Model for Constraining COVID-19 Infection Risk in Restaurants

Abstract

Since September 2021, because of the COVID-19 pandemic, the Japanese government has heavily limited business practices in the restaurant industry. While many restaurants operate in accordance with the guidelines for preventing the spread of COVID-19, the details of operation during business hours are left to each restaurant. In particular, as social distancing significantly contributes to reducing the infection risk, a common strategy is that an operator restricts the available seats in advance and then allocates customers. However, the effectiveness of seat allocation for reducing the infection risk is not always the same due to the situation in each restaurant; for example, the number of customers and their relative positions are always changing. Hence, an operator can effectively reduce the infection risk by determining a seat layout dynamically, as opposed to traditional methods. In addition, the magnitude of risk intended by an operator may change according to the situation in the restaurant, social conditions, and so on. Therefore, this study proposes an operational model for restaurants to reduce the magnitude of infection risk using a simplified parameter θ. The parameter θ is the threshold of infection risk for the entire restaurant space for an arbitrary time. By simulating the proposed model in a virtual restaurant, it is confirmed that the model can easily control the infection risk using a single parameter and contribute remarkably to reducing the infection risk with a slight loss of proceeds.