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Title:Application of a Multi-Agent System with the Large-Scale Agent-Based Model for Freight Demand Modeling
Authors:EunSu Lee and Ali Rahim-Taleqani
Publication Date:Nov 2018
Report #:MPC-18-370
Project #:MPC-458
TRID #:01692016
Keywords:agricultural products, freight traffic, grain, logistics, multi-agent systems, supply chain management, travel behavior, travel demand, travel patterns



To support agricultural logistics and energy development, road and bridge infrastructure has been in North Dakota due to the recent oil boom and the long-term importance of the agricultural industry. With the advance of simulation and data mining, the agent-based model (ABM) has emerged as a solution. Agent-based modeling techniques reflect a high level of detail for travel patterns in a region or state.

This research will review state-of-the-art ABM in transportation, determine an agent's travel behavior in rural and small urban freight movement, design a multi-agent system, and investigate applicability of the agent's travel behavior to statewide freight demand mode.

This paper outlines an agent-based freight transportation model of the grain upstream supply chain for Cass County in North Dakota. The objective is to develop a model incorporating stochastic variables to capture the uncertainties each entity faces, and consequently the effects of variables and strategies on traffic flows. This model simulates a robust level of the decision-making process at a granular level to assess the impact of cargo policy at local, state, regional, and national scales.

How to Cite

Lee, EunSu, and Ali Rahim-Taleqani. Application of a Multi-Agent System with the Large-Scale Agent-Based Model for Freight Demand Modeling, MPC-18-370. North Dakota State University - Upper Great Plains Transportation Institute, Fargo: Mountain-Plains Consortium, 2018.

NDSU Dept 2880P.O. Box 6050Fargo, ND 58108-6050