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This paper employs a novel hill-climbing algorithm to generate optimized legislative district maps. The algorithm allows users to specify one or multiple objectives with custom weights to be used in the optimization. Using this ability, we explore whether is it easier for Republicans or Democrats gain seats through partisan gerrymandering of US Congress across a range of states and under a range of other objective function constraints.