Implementation of novel model based on Genetic Algorithm and TSP for path prediction of pandemic

Abstract

The present study proposes a proposed algorithm in order to predict the moving-path of infectious diseases in Korea based on Traveling Salesman Problem (TSP) and Genetic Algorithm (GA). This system considers the changing elements of environments to trace the path of diseases by setting different intercity error rate. In particular, it includes transportation as the diseases' movement method showing the rapid change in modern society. Movement patterns are reviewed with environmental elements such as mountains and rivers around the site considered. This study allows us to detect the infection of the area and use vaccine more efficiently through the estimation of disease expansion areas. It may reduce not only direct treatment cost but also indirect expenses nationally. It can be used as important materials for effective control as it allows us to make strategic plans to respond against contagious diseases in advance.