Integrating storage location and order picking problems in warehouse planning

Storage location and order picking are two interdependent problems arising in warehouse planning traditionally solved independently. We introduce and model the integrated storage location and order picking problem and four special cases with imposed routing policies (return, S-shape, midpoint and largest gap). Experiments show that these models are difficult to solve, even for small warehouses and few orders. Therefore, we present a General Variable Neighborhood Search metaheuristic, which is observed to be very efficient for those small instances. For larger warehouses and more pickings, we show that our metaheuristic significantly improves solutions generated by common storage policies.