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A storage assignment approach considering SKU repetitions in sequential zone picking

Year: 2025
Type: article
Abstract: Background: Sequential zone picking systems often suffer from inefficiencies when high-demand variability coincides with a small set of distinct stock-keeping units (SKUs). Introducing SKU repetitions – placing identical SKUs in multiple zones – can mitigate imbalances between zones, but poses a complex storage-assignment challenge. When an order includes a SKU stored in multiple zones, a decision must be made regarding the optimal zone from which to pick it. Methods: The storage assignment problem with SKU repetitions is modeled as a binary program. Since the model formulation is NP-hard, a three-stage heuristic storage assignment approach is proposed, that explicitly anticipates downstream order-routing decisions. First, a decision is made how often each SKU is repeated. Then SKUs are grouped based on their co-occurrence in the order file. A variable neighborhood search iteratively relocates SKUs across zones to balance pick-face density and inter-zone travel times. Performance is assessed via a simulation calibrated with real-world HelloFresh order and facility data . Results: The proposed heuristic outperforms benchmark approaches on average by up to 19.5%. Besides, the simulation study shows that minor number of SKU repetitions can significantly improve overall ZPS performance. Finally, the algorithm is tested in a real-world ZPS showing up to 40% efficient gains in zone workload balancing. Conclusion: Anticipatory, storage assignment considering SKU repetitions significantly enhances ZPS efficiency. The proposed heuristic is computationally tractable and practically implementable, offering logistics managers clear guidelines for setting SKU repetition levels.
DOI: 10.1016/j.cie.2025.111482
Language: English
Open Access status: hybrid
Estimated APC paid: $3,790
OpenAlex ID: W4413860204
FWCI: 0.51
Cites: 21
Cited by: 1
Related to: 10