Assignment of Freight Traffic in a Large-scale Intermodal Network under Uncertainty

Uddin, Majbah; Huynh, Nathan N.; Ahmed, Fahim

doi:10.54175/hsustain3010001

Title: Assignment of Freight Traffic in a Large-scale Intermodal Network under Uncertainty

Journal Article · Thu Dec 28 00:00:00 EST 2023 · Highlights of Sustainability

DOI:https://doi.org/10.54175/hsustain3010001· OSTI ID:2267631

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Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Univ. of Nebraska, Lincoln, NE (United States)
South Carolina Department of Transportation, Columbia, SC (United States)

This paper presents a methodology for freight traffic assignment in a large-scale road-rail intermodal network under uncertainty. Network uncertainties caused by natural disasters have dramatically increased in recent years. Several of these disasters (e.g., Hurricane Sandy, Mississippi River Flooding, and Hurricane Harvey) severely disrupted the U.S. freight transportation network, and consequently, the supply chain. To account for these network uncertainties, a stochastic freight traffic assignment model is formulated. An algorithmic framework, involving the sample average approximation and gradient projection algorithm, is proposed to solve this challenging problem. The developed methodology is tested on the U.S. intermodal network with freight flow data from the Freight Analysis Framework. The experiments consider three types of natural disasters that have different risks and impacts on transportation networks: earthquakes, hurricanes, and floods. It is found that for all disaster scenarios, freight ton-miles are higher compared to the base case without uncertainty. The increase in freight ton-miles is the highest under the flooding scenario; this is because there are more states in the flood-risk areas, and they are scattered throughout the U.S.

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Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 2267631

Journal Information:: Highlights of Sustainability, Vol. 3, Issue 1; ISSN 2696-628X

Publisher:: Highlights of ScienceCopyright Statement

Country of Publication:: United States

Language:: English

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42 ENGINEERING
freight assignment
intermodal freight transport
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network uncertainty
stochastic programming
sample average approximation

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