Critical infrastructure resilience has become a national priority for the U.S. Department of Homeland Security. Rapid and efficient restoration of service in damaged transportation networks is a key area of focus. The intent of this paper is to formulate a bi-level optimization model for network recovery and to demonstrate a solution approach for that optimization model. The lower-level problem involves solving for network flows, while the upper-level problem identifies the optimal recovery modes and sequences, using tools from the literature on multi-mode project scheduling problems. Application and advantages of this method are demonstrated through two examples.

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The construction of a suite of consequence scenarios that is consistent with the joint distribution of damage to a lifeline system is critical to properly estimating regional loss after an earthquake. This paper describes an optimization method that identifies a suite of consequence scenarios that can be used in regional loss estimation for lifeline systems when computational demands are of concern, and it is important to capture the spatial correlation associated with individual events. This method is applied to a realistic case study focused on the highway network in Memphis, Tennessee, within the New Madrid Seismic Zone. This case study illustrates that significantly fewer consequence scenarios are needed with this method than would be required using Monte Carlo simulation.

Protecting infrastructures against natural hazards is a pressing national and international problem. Given the current budgetary climate, the ability to determine the best mitigation strategies with highly constrained budgets is essential. This papers describes a set of computationally efficient techniques to determine optimal infrastructure investment strategies, given multiple user objectives, that are consistent with an underlying earthquake hazard. These techniques include: optimization methods for developing representative events to characterize the hazard and the post-event condition of infrastructure components, a simulation model to characterize post-event infrastructure performance relative to multiple user objectives, and a multi-objective optimization algorithm for determining protection strategies. They are demonstrated using a case study of the highway network in Memphis, Tennessee.

The performance of a multi-layered security system, such as those protecting high-value facilities or critical infrastructures, is characterized using several different attributes including detection and interruption probabilities, costs, and false/nuisance alarm rates. The multitude of technology options, alternative locations and configurations for those technologies, threats to the system, and resource considerations that must be weighed make exhaustive evaluation of all possible architectures extremely difficult. This paper presents an optimization model and a computationally efficient solution procedure to identify an estimated frontier of system configuration options which represent the best design choices for the user when there is uncertainty in the response time of the security force, once an intrusion has been detected. A representative example is described.