Integrating storage location and order picking problems in warehouse planning. (August 2020) - Silva, Allyson; Coelho, Leandro C.; Darvish, Maryam; Renaud, Jacques
Highlights: We integrate the storage location and order picking problems in ware- house planning. Non-linear programming models are presented for the problem and four special cases. A General Variable Neighborhood Search metaheuristic is developed to solve them. We test our algorithms on generated instances similar from literature. The integrated problem significantly improves solutions compared to common policies. Abstract: 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.