Evacuation Path of Patients with Infectious Disease based on Three Algorithms

Abstract

With the global spread and deterioration of the coronavirus and monkeypox viruses, how to prevent the spread of infectious viruses in large public enclosed spaces has become a focus of public attention. This paper examined the distinctions between the evacuation of patients with infectious diseases and the evacuation of people in general disaster situations, using the outpatient center of a large hospital in China as the background. The three aspects of a new systematic method that is outlined in-depth step by step for solving this special patient evacuation problem are building the architectural space grid model, determining the objective function, and obtaining and comparing the optimization method. The shortest path is determined as the objective function, and three algorithms, namely the improved genetic algorithm, the traditional ant colony algorithm, and the Dijkstra algorithm, are used to optimize the path. While considering the number of people affected in the evacuation process, and together with the software running time as performance indexes, the results obtained from the three algorithms are evaluated, which shows that the patient evacuation path by Dijkstra’s algorithm is better. This study is of great relevance to hospitals, which gather more groups with low resistance and a higher possibility of virus infection, and it is also applicable to other large public places.