  A heuristic greedy algorithm is developed for efficiently tiling spatially
dense redshift surveys. In its first application to the Galaxy and Mass
Assembly (GAMA) redshift survey we find it rapidly improves the spatial
uniformity of our data, and naturally corrects for any spatial bias introduced
by the 2dF multi object spectrograph. We make conservative predictions for the
final state of the GAMA redshift survey after our final allocation of time, and
can be confident that even if worse than typical weather affects our
observations, all of our main survey requirements will be met.
