ArticleIndustrial & engineering chemistry research2026
A Biobjective Stochastic Model for Intermodal Supply Chains: Application to the Corn and Soybean Flows.
Article in Industrial & engineering chemistry research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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6 authors.
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Abstract
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 CO
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