Computes experimental designs for a two-arm experiment with covariates by greedily optimizing a balance objective function. This optimization provides lower variance for the treatment effect estimator (and higher power) while preserving a design that is close to complete randomization. We return all iterations of the designs for use in a permutation test. Additional functionality includes using branch and bound optimization (via Gurobi) and exhaustive enumeration.