Organizations returning to in person work after the coronavirus pandemic will face significant challenges in scheduling meetings and managing population density. We identified the potential to use optimization techniques to aid organizations in assigning meeting locations to reduce the hallway traffic, interactions, and potential to spread disease as people move between meetings.
What it does
The project uses convex optimization techniques to minimize the squared number of individuals who cross a path while traveling between rooms. We optimize with respect to the room in which a meeting is assigned. Our website takes an input dataset which consists of a network graph describing the locations of the meeting rooms, the routes between them, and room capacities, a table of people in the organizations and their home-room, and a table of meetings to be assigned to rooms, including their attendees. We then compute the shortest path between every pair of locations in the network, then format a minimization problem, which assigns each meeting to a room, respecting meeting capacities, and minimizes congestion along routes between locations. The project then outputs the room assignments for each meeting and a score identifying how many interactions originate from a meeting, which can be used to identify high-consequence meetings to move online.