Application of a Multi-Agent System With the Large-Scale Agent-Based Model for Freight Demand Modeling
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2018-11-01
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Abstract: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.
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