Optimization and Analysis of the Impact of Food Hub Location on GHG Emissions in a Short Food Supply Chain

The trend in many countries is to promote local consumption of food. This is done by encouraging consumers to connect directly with local farmers or by building hubs that are known as food hubs. Most of the studies on the environmental impact of short food supply chains (SFSCs) focus on the evaluation the greenhouse gas (GHG) emissions in SFSCs where consumers are directly connected to local farmers. Also, these studies mainly focus on GHG emissions due to transportation. To the best of our knowledge, there is no previous study or theoretical models on the estimation and impact of food hub selection and design on total GHG emissions, although they can play an important role in economic, environmental, and social sustainability of an SFSC. In this paper, we develop a framework to estimate GHG emissions from hubs and transportation in a two-echelon SFSC. We introduce a novel approach that utilizes piece-wise linear functions to model the hubs' GHG emissions combined with an optimization model to calculate the total GHG emission of the SFSC. With this approach, we address the gaps in the literature for a more realistic supply chain model. Our optimization-based approach determines the optimal location, size, and number of food hubs to minimize total GHG emissions. We apply this framework, under various conditions, to the design of a particular SFSC in the Normandy region of France. We also extend the study to other countries. We provide several numerical results that are then analysed. Our analysis shows that the number of foods hubs, their location, and their design may considerably impact the total GHG emissions, depending on the input parameters and data. Furthermore, this study contributes to the advancement of sustainable and green supply chain management, providing valuable insights for practitioners and policy makers aiming to optimize SFSCs for environmental sustainability.