Establishing Best Pedestrian Paths considering SARS-CoV-2 contagions: Mathematical Optimization Model and Mobile Application Approach

Abstract

Given the modern SARS-CoV-2 coronavirus pandemic and the Universidad de Los Andes needs to protect their students against possible contagions at the university campus, we established and design a mobile application to obtain the best route between two places in the campus university for a student. The resulting path obtained by our proposed solution reduces the distance traveled by the student as well as a possible coronavirus contagion during his journey through the university campus. Therefore, we modeled two types of costs: a transport cost that models the distance to travel the campus by a student, and the contagion risk cost that models the contagion susceptibility that a student has during a displacement through the campus. As a result, we developed and validated a solution algorithm that minimizes the two modeled costs. The algorithm results were compared against a Multi-Objective mathematical optimization solution were findings show an solution approximation between the algorithm and the mathematical model. Finally, a mobile application was developed to map the optimal routes to displace between two points in the university campus given the solution algorithm.

Keywords

• COVID-19
• Graph
• Pedestrian Traffic
• Transport function
• Interaction function
• Bi-objective problem