Natural aggregation processes such as the familiar flocking of birds have been accurately modeled using a simple, decentralized controller. Variations on this "boid" controller typically involve three or more control laws, each with an associated control gain and sensor range. In this paper, the boid controller is fitted with an additional rule designed to produce aerodynamically-efficient formations, such as those exploited by migratory birds and hypothetical unmanned aerial vehicles. A simple genetic algorithm is then used to optimize the control parameters for minimum power consumption in a flock of simulated birds. This report focuses on the development and utility of the flocking simulator as a fitness function for the GA. Preliminary results indicate that average power consumption can be significantly reduced with the modified, optimized boid controller.