A simulated annealing approach to optimal storing in a multi-level warehouse
This work addresses warehouse efficiency for logistics and manufacturing, but it is incremental as it applies a known optimization method to a specific domain.
The paper tackled the problem of optimizing storage assignments in multi-level warehouses to reduce retrieval times, achieving a 21% reduction compared to frequency-based assignments in experiments with over 4000 batched orders.
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.