  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.
