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The outbreak of coronavirus disease 2019 (COVID-19) has led to significantchallenges for schools, workplaces and communities to return to operationsduring the pandemic, requiring policymakers to balance individuals' safety andoperational efficiency. In this paper, we present our work using mixed-integerprogramming and simulation for redesigning routes and bus schedules forUniversity of Michigan (UM)'s campus bus system during the COVID-19 pandemic.We propose a hub-and-spoke design and utilize real data of student activitiesto identify hub locations and bus stops to be used in the new routes. Using thesame total number of buses to operate, each new bus route has 50\% or fewerseats being used and takes maximumly 15 minutes, to reduce disease transmissionthrough expiratory aerosol. We sample a variety of scenarios that covervariations of peak demand, social-distancing requirements, and break-downbuses, to demonstrate the system resiliency of the new routes and schedules viasimulation. The new bus routes are implemented and used by all UM campusesduring the academic year 2020-2021, to ensure social distancing and shorttravel time. Our approach can be generalized to redesign public transit systemswith social distancing requirement during the pandemic to reduce passengers'infection risk.

An Optimization-and-Simulation Framework for Redesigning University Campus Bus System with Social Distancing