The objective of this research is to explore how optimization can be used to explore locate military assets on a network and dispatch the assets to spatially-located and prioritized calls for service. To meet this objective, we formulate new discrete optimization models and algorithms that provide new capabilities for military transportation systems by exploring new models and algorithms for making integrated resource allocation decisions. This research has direct application to locating and dispatching military aeromedical evacuation systems (medevacs). The key contribution of this approach is that it provides an important step toward integrating complex military transportation systems for improving survivability by explicitly focusing on survival by investigating two interrelated, traditional problems, namely, how to locate and dispatch servers. This project's novelty lies in including five important features in the modeling framework that have not been considered in combination in the literature. In particular, this research: (1) explores new modeling paradigms that explicitly link soldier casualties (i.e., survivability) to resource allocation decisions; (2) considers multiple types of assets rather than a fleet of indistinguishable assets; (3) allows for geography-dependent parameters (e.g., travel times); (4) prioritizes potential customers by need; and (5) balances multiple criteria such as effectiveness with vulnerability.