A Spatial Optimization Approach for Simultaneously Districting Precincts and Locating Polling Places

Abstract

Voting is the most basic form of political participation. The agencies that are responsible for voting must delineate precincts and designate a polling place for each precinct. This spatial decision-making requires a strategic approach for several reasons. First, changes in the location of polling places induce transportation and search costs from the perspective of voters. Second, improving accessibility to polling places can increase turnout. Third, differences in the population sizes of precincts may produce biased voting results. Spatial optimization approaches can be a strategic method for delimiting precincts and siting polling places. The purpose of this paper is to develop a spatial optimization model, namely, the capacitated double p-median problem with preference (CDPMP-P), which simultaneously delimits boundaries of precincts and selects potential facilities in terms of mixed integer programming (MIP). The CDPMP-P explicitly includes realistic requirements, such as population balance, the spatial continuity of precincts, the preferences of potential facilities where polling places can be installed, and the possibility of allocating multiple polling places in one facility.