Order batch picking optimization under different storage scenarios for e-commerce warehouses

To improve the operational efficiency of e-commerce warehouses, multi-location storage systems which means each stock keeping unit can be stored in multiple locations or a location can contain multiple stock keeping units, have been developed and applied in practice. When orders are picked in a batch, how to select the picking location from storage locations holding the identical stock keeping unit obviously affects how far the pickers must travel to complete the picking tasks. However, few works have systematically studied how to optimize order batch picking from the perspective of different storage systems. This paper formulated the order batch picking optimization problems for three typical storage systems and developed the algorithm package including location interval distance algorithm, location selection algorithm, routing algorithm and order batching algorithm to tackle them. Our work is particularly capable to covering the situation of multi-location storage system. The numerical experiment results show that the performance of the proposed algorithm combinations is satisfactory to solve the problems with different size both in solution quality and computation efficiency. The applicable algorithm combinations used in practice are also recommended by comparative analysis. Our study can provide valuable decision reference to warehouse managers for operating batch picking system especially under multi-location scenarios efficiently.