  Gerrymandering, the deliberate manipulation of electoral district boundaries
for political advantage, is a persistent issue in U.S. redistricting cycles.
This paper introduces and analyzes a new phenomenon, 'votemandering'- a
strategic blend of gerrymandering and targeted political campaigning, devised
to gain more seats by circumventing fairness measures. It leverages accurate
demographic and socio-political data to influence voter decisions, bolstered by
advancements in technology and data analytics, and executes better-informed
redistricting. Votemandering is established as a Mixed Integer Program (MIP)
that performs fairness-constrained gerrymandering over multiple election
rounds, via unit-specific variables for campaigns. To combat votemandering, we
present a computationally efficient heuristic for creating and testing district
maps that more robustly preserve voter preferences. We analyze the influence of
various redistricting constraints and parameters on votemandering efficacy. We
explore the interconnectedness of gerrymandering, substantial campaign budgets,
and strategic campaigning, illustrating their collective potential to generate
biased electoral maps. A Wisconsin State Senate redistricting case study
substantiates our findings on real data, demonstrating how major parties can
secure additional seats through votemandering. Our findings underscore the
practical implications of these manipulations, stressing the need for informed
policy and regulation to safeguard democratic processes.
