Longer-term forecasting and risks in spatial optimization models: The world grain trade

This study develops a methodology to quantify risks associated with projected commodity flows in a spatial optimization model. In this paper it is applied to the world grain trade which is characteristic of numerous commodities and with complicated and competing logistical channels in world trade. The model provides a longer-run solution by simultaneously allowing for changes in production patterns, trade flows, and intermodal, interport and inter-reach allocation of shipments. Results show that important factors affecting shipments include: changes in demand across countries, delay costs, and the increased domestic use of grains. Findings of interest show delay costs on barges shift movements to rail, other origins and ports. Second, there is much greater uncertainty for projections for more distant periods forward. Finally, the model can be applied similarly to other commodities and/or be used to analyze spatial flows concentrated in other geographic regions.