Average performance of quasi Monte Carlo methods for global optimization

We compare the average performance of one class of low-discrepancy quasi-Monte Carlo sequences for global optimization. The Weiner measure is assumed as the prior probability on all optimized functions. We show how to construct van der Corput sequences and we prove their consistency. Numerical experimentation shows that the van der Corput sequence in base 2 has a better average performance.