Abstract
Designs with low discrepancy are of interest in many areas of statistical work. U—type designs are among the most widely studied design classes. In this paper a heuristic global optimization algorithm, Threshold Accepting, is used to find optimal U—type designs (uniform designs) or at least good approximations to uniform designs. As the evaluation of the discrepancy of a given point set is performed by an exact algorithm, the application presented here is restricted to small numbers of experiments in low dimensional spaces. The comparison with known optimal results for the two—factor uniform design and good designs for three to five factors shows a good performance of the algorithm.
Research was supported by the Deutsche Forschungsgemeinschaft, Sonderforschungsbereich 178, “Internationalisierung der Wirtschaft” at the University of Konstanz and a Hong Kong UGC grant. We are indebted to an anonymous referee for helpful comments. All remaining shortcomings are our owns.
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Winker, P., Fang, KT. (1998). Optimal U—Type Designs. In: Niederreiter, H., Hellekalek, P., Larcher, G., Zinterhof, P. (eds) Monte Carlo and Quasi-Monte Carlo Methods 1996. Lecture Notes in Statistics, vol 127. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-1690-2_31
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DOI: https://doi.org/10.1007/978-1-4612-1690-2_31
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