Decomposition methods for restoring infrastructure systems

We consider a new class of integrated network design and scheduling problems, with important applications in the restoration of services provided by civil infrastructure systems after an extreme event. Critical services such as power, waste water, and transportation are provided by these infrastructure systems. The restoration of these services is necessary for the society to recover from the extreme event as quickly as possible. The class of integrated network design and scheduling problems considered by this work focuses on a set of selected arcs to install into an existing network (i.e., network design decisions) and then scheduling these arcs on a set of work groups. Unlike previous network design problems, the network must be operating at intermediate points in time so that the scheduling decisions associated with the design decisions have a significant impact on the objective of the problem. The operations of the network at intermediate points in time will be evaluated by determining the amount of satisfied demand in the network. We also discuss exact methods to solve this class of large scale optimization problems by employing decomposition techniques. Our methods are tested on a realistic data set representing the (disrupted) power infrastructure of New Hanover County, NC. These results indicate that our methods are capable of providing better computational performance to decision-makers.