Agent optimization systems have been used to find near optimal results for many intractable problems, including the Traveling Salesman problem and the Transit Route Network Design (TRND) problem. In the agent architectures used for these problems, agents collaborate by working with a common pool of solutions, creating, modifying, or destroying solutions in this pool. It has been posited that "adept destruction can compensate for inept construction" in these optimization systems . This paper proposes a Selective Solution Pool Pruning agent that manages the diversification and intensification of the agent search process. This agent is instantiated for a system that is designed to optimize the TRND problem for a de facto benchmark transit network. The optimization system results show the Selective Solution Pool Pruning agent provides an effective means for managing the search process.