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Optimizing Classroom Assignments to Reduce Non-essential Interactions Among University-Level Students During Pandemics

  • Mujahid N. Syed

摘要

Academic sectors involve students from multiple origins, multiple social circles, and different health conditions. During pandemics like COVID-19, a key challenge is to reduce non-essential interactions among students while they are at school/university. In this work, we focus on interactions that occur when university level students move between consecutive classes. Specifically, the interactions that arise during the movements of students between different university buildings via buses or cars. These types of movements are very critical during the pandemic because they are inevitable, and they occur simultaneously as well as periodically within small time window (10 to 15 min). Movement via buses is a hot spot for spreading viral diseases like COVID-19. Furthermore, high usage of cars/bikes during the 10 to 15 min class interval results in high traffic on campus roads, which in-turn leads to longer travel times of the buses (due to the road congestion). Nevertheless, having consecutive classes within walk-able range may reduce the above interactions. To sum, careful assignment of classrooms to courses reduces the above non-essential interactions. In this work, we present an mathematical modeling based approach that assigns classroom locations to courses such that the overall interactions are minimized. Specifically, we propose a novel mixed integer program (MIP) that minimizes the above interactions and incorporates behavior of the students. Numerical example is provided to showcase the implementation and effectiveness of the proposed MIP.