This paper describes simulations designed to test the relative efficiency of two different sequential auction mechanisms for allocating compute resources between users in a shared data-center. Specifically we model the environment of a data center dedicated to CGI rendering in which animators delegate responsibility for acquiring adequate compute resources to bidding agents that automously bid on their behalf. For each of two possible auction types we apply a genetic algorithm to a broad class of bidding strategies to determine a near-optimal bidding strategy for a specified auction type, and use statistics of the performance of these strategies to determine the most suitable auction type for this domain.