Carton Set Optimization in E‐commerce Warehouses: A Case Study
提出三阶段纸箱套装优化方法，包括订单立方化、纸箱分组和最优纸箱选择，在DHL仓库测试后使运输成本降低7%、纸箱利用率提高7.8%，并显著改善碳足迹。
In this study, a three‐stage methodology for carton set optimization in e‐commerce warehouses is proposed and evaluated on three DHL Supply Chain warehouses. The methodology includes order cubing, carton grouping, and optimal carton set selection. A modified largest area fits first algorithm for order cubing is proposed. For optimal carton set selection, a genetic algorithm with a novel crossover strategy is introduced. The results show that the proposed carton set optimization approach can improve the shipping cost and carton utilization by 7% and 7.8%, and considerably improve the carbon footprint of the operations, even when the number of carton types is not changed.