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We discuss, and give examples of, methods for randomly implementing someminimax robust designs from the literature. These have the advantage, overtheir deterministic counterparts, of having bounded maximum loss in large andvery rich neighbourhoods of the, almost certainly inexact, response modelfitted by the experimenter. Their maximum loss rivals that of the theoreticallybest possible, but not implementable, minimax design. The procedures are thenextended to more general robust designs. For two-dimensional designs we samplefrom contractions of Voronoi tessellations, generated by selected basis points,which partition the design space. These ideas are then extended tok-dimensional designs for general k.

Jittering and Clustering: Strategies for the Construction of Robust Designs