An Agent-based Supply Chain and Freight Transportation Model: Case Study For Chicago Metropolitan Area

The remarkable increase in freight movements and their significant impacts on transportation system, regional wellbeing and economic growth provide sufficient motivation to develop reliable analysis tools to estimate commodity flows between zones and forecast the future demand and trends of goods movements among regions. While the need to develop freight demand model to better facilitate infrastructure planning and policy development has been clearly recognized for some time, the current state of practice regarding the development of freight demand models lags behind those of passenger travel by a considerable margin. This paper outlines a behavioral agent-based supply chain and freight transportation model for the Chicago Metropolitan Area. This multimodal freight model addresses critical technical and conceptual hurdles that have challenged past efforts by applying agent-based framework in which firm-level decision making processes, including supply chain formation, are simulated at the very disaggregate level. The study tries to demonstrate the use of disaggregate, behavioral-based modeling approaches for evaluating freight policy impacts at the national/regional scale.