The inefficiencies observed in current agro-food supply chains, and recent trends in agro-food industry such as consolidation, increase the need for further studies on supply chain management in this field. Models are required for the complex task of determining the optimal supply chain configuration in order to improve their economic and environmental performance, while taking into account the specific characteristics of agro-food supply chains. This paper provides a general description of the supply chain design problem in agro-food industrial chains, considering the role of seasonality and harvesting decisions, perishability, and processing. A general model formulation is presented, which accommodates for these characteristics and for forward and backward flows along the chain. The general model is applied to a case study of the sugar beet processing chain in the Netherlands. The pareto-efficient frontier between maximizing the total gross margin and minimizing the global warming potential in CO2-eq is explored. Uncertainties in demand and harvest yield are taken into account using a stochastic version of the model. Results show that a supply chain design model tailored to the specific characteristics of an agro-food supply chain with its uncertainties leads to identifying better performing supply chain configurations. In the case study, supply chain configurations can be found in which the performance on both the economic and the environmental objective is better than the modelled current performance. Additionally, we observe that supply chain configurations with decentralized processing or pre-processing are an interesting topic for future research in the context of agro-food industry.
