  We propose a simulated annealing algorithm specifically tailored to optimise
total retrieval times in a multi-level warehouse under complex pre-batched
picking constraints. Experiments on real data from a picker-to-parts order
picking process in the warehouse of a European manufacturer show that optimal
storage assignments do not necessarily display features presumed in heuristics,
such as clustering of positively correlated items or ordering of items by
picking frequency.
  In an experiment run on more than 4000 batched orders with 1 to 150 items per
batch, the storage assignment suggested by the algorithm produces a 21\%
reduction in the total retrieval time with respect to a frequency-based storage
assignment.
