A Biobjective Stochastic Model for Intermodal Supply Chains: Application to the Corn and Soybean Flows
Marco Marto, Valentina Chkoniya, Eduardo B. Couto, Telmo Pinto, Agostinho Agra, Marco S. Reis
TL;DR
This paper proposes a biobjective stochastic model to optimize the intermodal supply chains for corn and soybean distribution in Europe and North Africa, considering uncertainties in demand and costs.
Contribution
The novel contribution is a biobjective stochastic model integrating expected cost and CVAR constraints for intermodal supply chain optimization.
Findings
The port of Itaqui is strategically important for supply-side operations.
The port of Sines is identified as a key distribution hub for efficient intermodal networks.
Stochastic modeling helps manage uncertainties in demand and transportation costs.
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…
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Taxonomy
TopicsSupply Chain and Inventory Management · Supply Chain Resilience and Risk Management · Vehicle Routing Optimization Methods