The supply chain optimization model uses the MIP formulation proposed by Ma et al. to study the US Midwest region. Given the extremely large size of the MIP for the national-scale system that we study here, we conducted some simplifications to enable tractability. Specifically, transportation routes are limited to adjacent counties and we limit the size of technologies to a couple of options. These simplifications significantly reduce model complexity and solution time, but the scale of the problem still represents a challenge to state-of-the-art solvers. As such, here we compute close-tooptimal solutions and report the optimality gap of such solutions (which measures how far the solution is from the calculated upper bound on total profit) to justify that our designs are of high enough quality. Future work will aim to implement advanced algorithms that enable the solution of problems with a higher level of resolution and complexity.