Supplementary data for numerical experiments conducted in Cell Ag Supply Chain Design Paper

Cellular agriculture, which produces animal-derived products via biotechnological processes, has the potential to mitigate the negative impacts of traditional methods of meat and dairy production such as elevated greenhouse gas emissions, depletion and degradation of arable lands, and waterway pollution. However, lifecycle assessments for cultured meat production processes suggests that additional environmental and cost improvements are needed to compete with traditional meat production methods. Adoption of circular supply chains can improve the economic and environmental outcomes of production processes. In cultured meat production, the use of agricultural byproducts such as hydrolyzed soymeal, as a cheap alternative to chemically defined amino acids holds much promise for reducing cost and environmental impacts. However, their impact on production efficiency is largely unknown. The aim of this paper is to develop a novel exploratory supply chain model for a viable large-scale cellular agriculture network that considers facility location, ingredient blending, capacity design and technology selection problems. A mixed integer linear programming model is developed to investigate the dynamics between demand, capacity design, location, blending and technology selection decisions. Useful managerial insights are developed through various computational experiments including iso-cost curves to help decision-makers design the optimal blending of pure (pharmaceutically sourced) and chemically undefined byproduct ingredients.