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U.S. schools are heavily segregated by race and income. State and local policymakers face many potential policy options, such as redrawing attendance zones or merging school districts. However, scholars and policymakers lack accessible evidence on competing policies thanks to both the large set of possibilities facing them and the technical difficulties involved in creating maps that simultaneously meet many criteria. Further, wide variation in population patterns and school district geography across the United States suggests different policies may be most effective in different places. Adapting redistricting simulation methodology, I redraw geographic school assignments under a set of potential policies. My implemented framework allows for the optimization of certain criteria — like racial integration or income balance — while maintaining other constraints, such as using existing school facilities and minimizing travel times.