We give an upper bound for the average complexity (i.e. the expected number of steps until termination) for a continuous random search algorithm using results from renewal theory. It is thus possible to show that for a predefined accuracy ε, the average complexity of the algorithm is O(–log ε) for ε → 0 which is optimal up to a constant factor.