All road authorities are required to make sound maintenance investment decisions to maximise value from available budgets. As an indication of the complexity of this task, the schedule of pavement maintenance and rehabilitation for a small pavement network consisting of 200 segments, with four treatment alternatives over a planning period of five years has (2004)5 = 1.05 * 1046 possible alternatives. This study investigates the number and quality of solutions obtained by adding additional computing resources to a budget constrained implementation of a Parallel Genetic Algorithm based pavement management treatment scheduling system.