As systems become more interconnected, the focus of engineering design must shift to include consideration for systems of systems (SoS) e ects. As the focus shifts from singular systems to systems of systems, so too must the focus shift from performance based analysis to an evaluation method that accounts for the tendency of such large scale systems to far outlive their original operational environments and continually evolve in order to adapt to the changes. It is nearly impossible to predict the nature of these changes, therefore the rst focus of this thesis is the measurement of the exibility of the SoS and its ability to evolve and adapt. Flexibility is measured using a combination of network theory and a discrete event simulation, therefore, the second focus is the development of a simulation environment that can also measure the system's performance for baseline comparisons. The results indicate that simulated exibility is related to the performance and cost of the SoS and is worth measuring during the design process. The third focus of this thesis is to reduce the computational costs of SoS design evaluation by developing heuristics for exibility. This was done by developing a network model to correspond with the discrete event simulation and evaluating network properties using graph theory. It was shown that the network properties can correlate with simulated exibility. In such cases it was shown that the heuristics could be used in connection with an evolutionary algorithm to rapidly search the design space for good solutions. The entire methodology was demonstrated on a multi-platform maintenance planning problem in connection with the Navy Hardware Open System Technologies initiative.