The multi-modal freight transportation network plays an important role in the economic vitality of states, regions, and the broader country. The functionality of this network is threatened by disruptive events that can disable the capacity of the network to enable flows of commodities in portions of nodes and links. This work integrates a multi-commodity network flow formulation with an economic interdependency model to quantify the multi-industry impacts of a disruption in the transportation network to ultimately measure and assess the importance of network components. The framework developed here can be used to measure the efficacy of strategies to reduce network vulnerability from the unique perspective of multi-industry impacts. The framework is illustrated with a case study considering the multi-modal freight transportation network consisting of inland waterways, railways, and interstate highways that connect the state of Oklahoma to surrounding states.
All Science Journal Classification (ASJC) codes
- Computer Networks and Communications
- Artificial Intelligence