Strategic Investment Choice to Reduce Disruptions and Increase Resiliency of Roadway Freight Network

The proposed research will develop models and algorithms to identify systematic investment strategies by reducing link disruption failure probabilities and enhancing overall roadway resilience for freight flows. A new stochastic programming modeling framework will be developed in which disruption probabilities depend on resource allocation decision variables and new algorithms will be developed to deal with the computational challenges caused by both the large number of scenarios and the nonlinearity in both first-stage and second-stage sub-problems. The framework, including data integration, models, and solution methods, will be programmed and tested with a case based on the freight network in the State of Tennessee.

• Record URL:
  • https://fersc.utk.edu/research-focus/fersc-projects-year-3/

Language

• English

Project

• Status: Active
• Funding: $225,000.00
• Contract Numbers:

  69A3552348338

• Sponsor Organizations:

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Managing Organizations:

  Center for Freight Transportation for Efficient and Resilient Supply Chain

  University of Tennessee Knoxville
  Knoxville, TN  United States  37996
• Project Managers:

  Bruner, Britain

  Kaplan, Marcella

• Performing Organizations:

  University of Tennessee, Knoxville

  Knoxville, TN  United States 
• Principal Investigators:

  Jin, Mingzhou

• Start Date: 20250901
• Expected Completion Date: 20260831
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers Program

Subject/Index Terms

• TRT Terms: Algorithms; Freight transportation; Predictive models; Service disruption; Stochastic programming; Trucking
• Geographic Terms: Tennessee
• Subject Areas: Data and Information Technology; Freight Transportation; Planning and Forecasting;

Filing Info

• Accession Number: 01984334
• Record Type: Research project
• Source Agency: Center for Freight Transportation for Efficient and Resilient Supply Chain
• Contract Numbers: 69A3552348338
• Files: UTC, RIP
• Created Date: Mar 25 2026 4:46PM