Network design for local agriculture using robust optimization

Abstract

For small farmers wishing to sell their products under the “local agriculture” marketing concept, connecting with consumers can be challenging. One approach to mitigating this disconnect between where production occurs and where consumers reside is through a network of regional consolidation points. In this study, we utilize optimization models to assist the Missouri Coalition of Environment (MCE) in helping farmers from Missouri and Illinois route products from their farms to a central hub in St. Louis. The aim of this study was to minimize the ton-miles traveled by farmers and MCE vehicles in delivering agricultural products from farms to regional hubs to the central hub. Given historical data about variability of plant and animal production in the Greater Plains region, a robust optimization approach was incorporated to increase the likelihood that the network can accommodate uncertainty in agricultural production. GAMS/CPLEX was used to solve the model under different configurations and identify potential locations for regional hubs. Computational testing determined that the capacity of hubs plays a key role in the optimal assignments: given the assumed model constraint that farmers can travel only to their nearest regional hub, solutions may sacrifice a better objective function value in order to accommodate farmers’ travel requirements.

Keywords

• Optimization
• Robustness and sensitivity analysis
• Supply chain management