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.
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机译：我们比较了一类低差异准蒙特卡罗序列的全局平均性能。 Weiner度量被假定为所有优化函数的先验概率。我们展示了如何构建范德科普特序列，并证明了它们的一致性。数值实验表明，基数为2的van der Corput序列具有较好的平均性能。
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