We propose symmetric Latin hypercubes for designs of computer experiment. The goal is
to oer a compromise between computing eort and design optimality. The proposed class of
designs has some advantages over the regular Latin hypercube design with respect to criteria
such as entropy and the minimum intersite distance. An exchange algorithm is proposed for
constructing optimal symmetric Latin hypercube designs. This algorithm is compared with two
existing algorithms by Park (1994. J. Statist. Plann. Inference 39, 95 –111) and Morris and
Mitchell (1995. J. Statist. Plann. Inference 43, 381– 402). Some examples, including a real case
study in the automotive industry, are used to illustrate the performance of the new designs and
the algorithms.
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