  The deployment of several large scale arrays is envisioned to study
astroparticles at ultra-high energies. In order to circumvent the heavy
computational costs of exploring and optimizing their layouts, we have
developed a pruning method. It consists in i) running a set of microscopic
simulations and interpolate them over a dense, regularly spaced array of
detection units, and ii) pruning the unnecessary units out of the layout, in
order to obtain the shower footprint on a newly shaped layout. This method
offers flexibility to test various layout parameters, instrumental constraints,
and physical inputs, with a drastic reduction in the required CPU time. The
method can be universally applied to optimize arrays of any size, and using any
detection techniques.
  For demonstration, we apply the pruning tool to radio antenna layouts, which
allows us to discuss the interplay between the energy and inclination of
air-showers on the size of the radio footprint and the intensity of the signal
on the ground. Some rule-of-thumb conclusions that can be drawn for this
specific case are: i) a hexagonal geometry is more efficient than a triangular
geometry, ii) the detection efficiency of the array is stable to changes in the
spacing between radio antennas around 1000m step size, iii) for a given number
of antennas, adding a granular infill on top of a coarse hexagonal array is
more efficient than instrumenting the full array with a less dense spacing.
