Network Optimization of Food Flows in the US

The world food system is a globalized and interconnected network, and prior research has shown the US is one of the most important countries within this global network. Considering this, any affects on the US food network might have far reaching implications. The objective of this paper is to show how the efficiency of the US food network can be optimized and to examine the tradeoffs between sustainability, efficiency, and resiliency in a network science based approach. To do this we use the 2012 US Commodity Flow Survey (CFS) data focusing on origin-destination flows for 5 categories of food. We interpret these origin-destination flows as a directed weighted network and use a linear programming (LP) based approach to reconfigure the flows in order to minimize the "food miles" in the network. We extend our LP to a multi-objective optimization problem in order to consider partially optimized solutions that are closer to the current food network. Finally, we calculate characteristics of the optimized networks and compare them to the original network. Our results show that the US food network has the potential for more than a 50% reduction in "food miles", which will result in a food system that is not only more economically efficient but also with a smaller sustainability impact by reducing the corresponding transportation GHG emissions.