A Multi-Objective Mathematical Model for Seating Plans in Public Places

Abstract

Social distance-based allocation models have gained importance since the advent of COVID-19 to minimize infection risk while continuing daily life. A multi-objective mathematical model with three objectives has been developed in this context. The proposed model considers various factors such as immune system, mask or vaccination status or air purifiers in the place to maximize the number of people while minimizing the total and maximum individual infection risk. The AUGMECON2 method is applied to the model and the model is applied in a real place. The results are analyzed using different parameters according to the immune system, mask or vaccination status of the allocated people. It has been observed that changing the parameters provides improvements of up to 45% in total and maximum individual infection risk. Thanks to Pareto sets obtained by the model, the decision-makers can make quick decisions between improved results.