A Biobjective Stochastic Model for Intermodal Supply Chains: Application to the Corn and Soybean Flows

Recently, several unexpected events of various types (geopolitical, economic, health-related, and weather-related) have had a significant global impact, affecting the lives of millions of people and businesses. Disruptions in supply chains highlight the importance of planning and managing them at various hierarchical levels of decision-making. This paper presents and analyzes supply chain networks (SCNs) for the distribution of soybean and corn in Europe and North Africa, considering the uncertainty of demand and costs along intermodal routes. Transportation and distribution costs for these commodities are minimized by considering the uncertainty of demand and transportation costs. Starting from a deterministic model to establish the SCN, uncertainty is then introduced through stochastic modeling, with the optimization goals redefined accordingly, more specifically in terms of expected cost (EC) and conditional value at risk (CVAR) constraints. The solutions of the bi-objective model, including equivalent average emissions CO₂, highlight the strategic positions of the port of Itaqui on the supply side and of the port of Sines as distribution hubs (transshipment) in the design of the networks according to the different objectives. The advantageous position of the port of Sines is analyzed in detail, according to the strategic objective of designing a more efficient intermodal SCN for the distribution of soybean and corn.