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Research Reports |
| 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 |
| Type: | Research Report – MPC Publications |
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.
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.
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