A Behavioral Agent-based Supply Chain and Freight Transportation Model: Application for Arizona Sun Corridor Megaregion
Corresponding Author: Zahra Pourabdollahi, RS&H
Presented By: Zahra Pourabdollahi, RS&H
Abstract
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 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 by transportation planners and researchers for some time, the current state of the practice regarding the development of freight demand models lags behind those of passenger counterparts by a considerable margin. The objective of this study is to fill the gap by developing a disaggregate freight movement analysis tool. This paper outlines a behavioral agent-based supply chain and freight transportation model for the Arizona Sun Corridor Megaregion, which is among the fastest growing megaregions in the country and a freight gateway to the international market. This multimodal freight model addresses critical technical and conceptual hurdles that have challenged past efforts by applying agent-based computational economics framework in which firm-level decision making processes, including supply chain formation, are simulated at the very disaggregate level. The study also utilizes the first generation of 2012 Commodity Flow Survey Microdata for developing a disaggregate joint model of mode and shipment size choice for the regional commodity flows to forecast main logistics choices of supply chains. The study tries to demonstrate the use of cutting-edge, behavior-based modeling approaches for evaluating freight policy impacts at the regional scale. This project was part of the SHRP2 C20 program: Freight Demand Model and Data Improvement for Maricopa Association of Governments.