Finding Pareto Efficient Redistricting Plans with Short Bursts

TL;DR

This paper extends a single-criterion redistricting optimization method to handle multiple criteria, enabling approximation of the Pareto frontier, and demonstrates its effectiveness and robustness in realistic scenarios.

Contribution

It introduces a multi-criterion extension of the short bursts method for redistricting, facilitating better tradeoff analysis in districting plans.

Findings

Method performs as expected in realistic settings

Algorithm is not very sensitive to parameters

Open-source implementation available

Abstract

Redistricting practitioners must balance many competing constraints and criteria when drawing district boundaries. To aid in this process, researchers have developed many methods for optimizing districting plans according to one or more criteria. This research note extends a recently-proposed single-criterion optimization method, short bursts (Cannon et al., 2023), to handle the multi-criterion case, and in doing so approximate the Pareto frontier for any set of constraints. We study the empirical performance of the method in a realistic setting and find it behaves as expected and is not very sensitive to algorithmic parameters. The proposed approach, which is implemented in open-source software, should allow researchers and practitioners to better understand the tradeoffs inherent to the redistricting process.