Measuring and maximizing resilience of freight transportation networks

In assessing a network's potential performance given possible future disruptions, one must recognize the contributions of the network's inherent ability to cope with disruption via its topological and operational attributes and potential actions that can be taken in the immediate aftermath of such an event. Measurement and maximization of network resilience that accounts for both in the context of intermodal freight transport are addressed herein. That is, the problem of measuring a network's maximum resilience level and simultaneously determining the optimal set of preparedness and recovery actions necessary to achieve this level under budget and level-of-service constraints is formulated as a two-stage stochastic program. An exact methodology, employing the integer L-shaped method and Monte Carlo simulation, is proposed for its solution. Optimal allocation of a limited budget between preparedness and recovery activities is explored on an illustrative problem instance involving a network abstraction of a United States rail-based intermodal container network.