Future military systems such a FCS require a robust and flexible network that supports thousands of ad hoc nodes; therefore, we must ensure the scalability of networking protocols (e.g., rout-ing, security and QoS). The use of hierarchy is a powerful solu-tion to the scaling problem, since it allows networking protocols to operate on a limited number of nodes, as opposed to the entire network. We have proposed an automated solution to dynami-cally create and maintain such hierarchy based on a combina-tion of global optimization algorithms [1] and local distributed maintenance protocols [2]. Global optimization clearly im-proves performance in a static network but, it is unclear how effective it is in a dynamic ad hoc environment. As network and node characteristics change, the optimization algorithm may use incomplete, stale, or even inaccurate metrics. In this paper, we analyze how the hierarchy created deteriorates from the optimal as network conditions change. We show that the fragility of the optimization depends on the particular cost function and the number of metrics that change. More important, we show, for the first time, that global optimization can remain effective for long periods with good cost functions, even in large dynamic ad hoc networks (where metrics may change rapidly due to node mobility and links making and breaking). This result shows that, with fast optimization algorithms such as modified Simulated Annealing [1], future military systems can use global optimiza-tion to autoconfigure domains to significantly improve perform-ance. We also show that local maintenance protocols support the global optimization mechanisms by extending the time the hierarchy remains feasible.