In the wake of a natural disaster, quickly reopening services and amenities is critical for community well-being and resiliency. However, in many situations, residents' access to essential services, such as gas stations, grocery stores, and medical clinics, is limited by the severity of the disaster and the quality of the recovery plan.  To improve the equity of access throughout the recovery period, and thus the speed with which a community recovers normalcy, we formulate an integer programming model to determine an optimal repair and reopening schedule for supermarkets after a natural disaster.

Concussions are a common brain injury, affecting millions of Americans each year but, the relationships between psychological symptoms and neurocognitive changes as a result of a concussion are not well understood. In order to further understand these relationships, we develop a network to analyze psychological symptoms and neurocognitive domains before a concussion, immediately following a concussion, and after recovery.   

In undersea warfare (USW) there is a need to allocate search assets in order to find the most valuable set of targets. Allocating search assets can be accomplished through building a mathematical model. However, poor assumptions regarding the search assets or the targets can cause subpar results upon implementation.  To combat subpar results we consider uncertainty in the mathematical model to develop a robust optimization model, capable of adapting in a dynamic environment, that will help theater USW commanders allocate limited search assets to detect a set of targets.