Modeling food supply chains using multi-agent simulation

In light of the pressures of increasing demands on earth's resources, society faces serious challenges in food production and distribution. Food supply chain (FSC) models are critically important, providing decision-makers with tools that allow for the evaluation and design of FSCs, en route to ensuring sustainable FSC productivity. Multi-agent simulation (MAS) is well-suited to modeling FSCs for this purpose, enabling capture of decision-making, interactions, and adaptations of autonomous FSC actors. However, certain characteristics of FSCs are particularly difficult to model in detail, as data requirements can be intensive. In this paper we highlight some of the challenges modelers face in deciding the most appropriate methods for representing the elements of an FSC in an MAS model. We provide examples from the literature that show how other modelers have chosen to address these challenges. Finally, we discuss benefits and limitations of each example's approach, in terms of realism and data requirements.