We Still Need to Fix That: A Queueing Theory Approach to Reducing Voter Wait Times

Abstract

This thesis provides a framework for improving voter experiences at the polling place using queueing theory and Monte Carlo simulation. It builds upon limited research applying elementary queueing theory techniques to apply more advanced modeling methods that more realistically reflect polling place dynamics and develops a customizable simulator that allows proposed changes to be quickly and rigorously tested. It also tests fluid diffusion and steady-state approximation techniques for traditional queues and demonstrates their limited applicability to the polling place problem. Through the application of this procedure to case studies of four distinct polling place environments, this thesis demonstrates the importance of implementing changes at the polling place-level, rather than the state- and national-level advocated in the literature, and the robustness of this procedure to a wide range of polling place problems.