Establishing Best Pedestrian Paths considering SARS-CoV-2 contagions: Mathematical Optimization Model and Mobile Application Approach
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.
Organización Mundial de la Salud, “Q&a. How is COVID-19 transmitted.” 2020.
Universidad de Los Andes, “Facts and figures.” https://planeacion.uniandes.edu.co/en/statistics/factsand-figures, 2019.
Universidad de Los Andes, “Campus en cifras.” https://campusinfo.uniandes.edu.co/es/campusencifras, 2019.
J. E. Cantor, C. Lozano-Garzón, and G. A. Montoya, “A multi-objective mathematical optimization model and a mobile application for finding best pedestrian routes considering SARS-CoV-2 contagions,” in Fourth international conference on applied informatics, 2021, pp. 191–206.
S. A. Muller, M. Balmer, A. Neumann, and K. Nagel, “Mobility traces and spreading of COVID-19.” https://www.medrxiv.org/content/10.1101/2020.03.27.20045302v1.full.pdf, 2020.
N. Kumar, J. B. Oke, and B. Nahmias-Biran, “Activity-based contact network scaling and epidemic propagation in metropolitan areas.” https://arxiv.org/abs/2006.06039, 2020.
Universidad de Los Andes, “Reporte de sostenibilidad 2019.” https://sostenibilidad.uniandes.edu.co/images/Reporte2019/Reporte-de-sostenibilidad-2019W.pdf, 2019.
G. J. working group, “GeoJSON.” https://geojson.org/, 2016.
M. Schultz and J. Fuchte, “Evaluation of aircraft boarding scenarios considering reduced transmissions risks.” https://www.mdpi.com/2071-1050/12/13/5329, 2020.
KNIME, “KNIME.” https://www.knime.com/, 2020.
Firebase Inc, “Firebase.” https://www.firebase.google.com/, 2012.
Python Software Foundation, “Python 3.6.” https://www.python.org/, 2020.
E. W. Dijkstra, “A note on two problems in connexion with graphs,” Numerische mathematik, vol. 1, no. 1, pp. 269–271, 1959.
Y. Haimes, L. Lasdon, and D. Wismer, “On a bicriterion formulation of the problems of integrated system identification and system optimization,” IEEE Transactions on Systems, Man, and Cybernetics, vol. SMC–1, no. 3, pp. 296–297, 1971.
W. Hart, J.-P. Watson, and D. Woodruff, “Pyomo.” https://pyomo.readthedocs.io/en/stable/, 2019.
World Wide Web Consortium, “Web services architecture.” 2004.
M. Grinberg, Flask web development: Developing web applications with python. O’Reilly Media Inc., 2018.
A. Asthana, A. Kane, and A. Sobti, “Postman API client.” https://www.postman.com/product/api-client/, 2014.
Google LLC, “Android pie.” https://www.android.com/versions/pie-9-0/, 2019.
JetBrains, “Kotlin.” https://github.com/JetBrains/kotlin/releases/latest, 2020.
Google LLC, “Maps SDK for android.” https://developers.google.com/maps/documentation/android-sdk/overview, 2020.
Freepik Company, https://www.flaticon.com/, 2020.
Google LLC, “Android volley.” https://developer.android.com/training/volley, 2020.
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