  Design of experiments, random search, initialization of population-based
methods, or sampling inside an epoch of an evolutionary algorithm use a sample
drawn according to some probability distribution for approximating the location
of an optimum. Recent papers have shown that the optimal search distribution,
used for the sampling, might be more peaked around the center of the
distribution than the prior distribution modelling our uncertainty about the
location of the optimum. We confirm this statement, provide explicit values for
this reshaping of the search distribution depending on the population size
$\lambda$ and the dimension $d$, and validate our results experimentally.
