Models for Mitigating Dynamic Risk in Multi-Modal Perishable Commodity Supply Chain Networks

Large-scale supply chain disruptions such as natural disasters, terrorist attacks, and transportation network failures can dramatically reduce supply chain effectiveness and result in significant economic loss. When the items in transit are perishable, an additional level of concern is introduced, as items that spoil or degrade in quality can result in an even greater economic loss. This project focuses on the development of mathematical models that maximize network resiliency when allocating scarce fortification resources for transportation infrastructure components in perishable commodity supply chain networks. The assessment of supply chain risk is from an all-hazards perspective, wherein potential disruptions include both unplanned (i.e., natural disasters) and planned, albeit dynamically changing, adversarial actions (i.e., an adversary with an adaptive, evolving objective). This project is differentiated from other research by its focus on inland waterway supply chains for perishable commodities. An additional distinguishing factor is that most previous research assumed disruptions were caused by an adversary whose objective was to maximize network disruption. Modeling efforts attempt to account for all-hazard disruption scenarios to mitigate dynamic risk caused by an adversary with an unknown, adaptive objective. The implementation efforts focus on bulk transportation of corn on inland waterways in the United States. The project is divided into three modeling phases. Phase I, focuses on models that allocate resources to waterway infrastructure components to increase resiliency when disruptions are caused by natural disasters. Phase II considers disruptions caused by an adversary with a known objective, and Phase III explores the formulation of models that incorporates the effects of an unknown adversarial objective.

• Corporate Authors:

  Mack Blackwell National Rural Transportation Center

  University of Arkansas, 4190 Bell Engineering Center
  Fayetteville, AR  United States  72702

  Department of Homeland Security

  Washington, DC  United States  20528
• Authors:
  • Baycik, Orkun
  • Bright, Julianna
  • Spicer, Jessica
  • St John, Dia
  • Ulesich, Morgan
  • Kitchens, Taylor
  • Mason, Scott
  • Milburn, Ashlea Bennett
  • Pohl, Edward A
  • Rainwater, Chase
• Publication Date: 2014-4-30

Language

• English

Media Info

• Media Type: Digital/other
• Features: Appendices; Figures; References;
• Pagination: 94p

Subject/Index Terms

• TRT Terms: Decision support systems; Hazards and emergency operations; Inland waterways; Mathematical models; Multimodal transportation; Perishables; Resource allocation; Risk management; Supply chain management
• Subject Areas: Freight Transportation; Marine Transportation; Planning and Forecasting; Security and Emergencies; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01529442
• Record Type: Publication
• Report/Paper Numbers: MBTC DHS 1109
• Contract Numbers: 2008-ST-061-TS003
• Files: TRIS
• Created Date: Jun 30 2014 9:41AM