Multi-agent simulation modeling of supplier selection for local food systems
Consumer demand for regionally-produced food has increased dramatically in the past decade, in response to concerns over food safety and quality, as well as the serious environmental, economic, and social equity issues that pervade the modern industrial food supply system. As demand grows, distributors of regionally-produced food (i.e., food hubs) face many challenges in their efforts to scale up, particularly with supply chain management. They must find ways to operate more efficiently without undermining their support for the regional farming community. In this paper we describe a multi-agent simulation model of a theoretical regional food system in which multiple farmer-agents produce food, negotiate with a regional food-hub-agent, and try to sell their food at the best possible price. Using this model, we compare the effects of various food hub supplier selection policies on system outcomes, in terms of food hub profitability, the cost of quality, transaction costs, the number of farmers required to satisfy demand, and the size distribution of these farmers. Results suggest that the food hub’s selection policy significantly impacts long-term system performance.
This proceeding was published as Bora, Hardik D., and Caroline C. Krejci. "Multi-agent simulation modeling of supplier selection for local food systems." In Proceedings of the 2015 IIE Annual Conference and Expo. Institute of Industrial Engineers (IIE). Pages 2586-2595. May 30-June 2, 2015, Nashville, Tennessee. Posted with permission.