Average performance of quasi Monte Carlo methods for global optimization

in this paper we compare the average performance of one class of low-discrepancy quasi-Monte Carlo sequences for global optimization. Weiner measure is assumed as the probability prior 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.