To guarantee high customer service and short and accurate lead times, many e-commerce retailers have started to home deliver their customer orders within a few hours or even minutes, also known as quick-commerce order fulfillment. Quick-commerce order fulfillment consists of three main processes: order picking in the warehouse, order batching for delivery, and last-mile delivery. The ultimate delivery performance depends on managing all three processes, which are highly stochastic, and interdependent. We capture this stochasticity and interdependency in an integrated analytical framework and derive approximate analytical expressions for the mean and variance of the total order fulfillment time. We validate the analytical expressions with both in-house detailed process simulations and external-party output measures. We then analyze the delivery cost-service quality trade-offs using an optimization model that minimizes the expected order fulfillment cost with a () constraint, focusing on meeting delivery time deadlines. The optimization model determines the number of pickers, the optimal delivery batch size, and the number of vehicles required to deliver the customer orders. Achieving a high delivery reliability comes at a cost. In comparison to the model with DP constraints, we observe that the expected order fulfillment cost averaged over all data parameter settings obtained from the model without DP constraints is 8.9% lower; however, the mean and standard deviation of order fulfillment time increase by 44.1% and 18.6%, respectively, which results in low delivery reliability. We further demonstrate that an integrated analysis of the order fulfillment process is essential to set reliable fulfillment due times.

中文翻译：

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具有交付时间承诺的集成订单履行流程的随机建模：订单拣选、批处理和最后一英里交付

为了保证优质的客户服务和短而准确的交货时间，许多电子商务零售商已开始在几小时甚至几分钟内将客户订单送货上门，也称为快速商务订单履行。快速商务订单履行由三个主要流程组成：仓库订单拣选、订单批量交付和最后一英里交付。最终的交付绩效取决于对所有三个流程的管理，这三个流程高度随机且相互依赖。我们在集成分析框架中捕捉这种随机性和相互依赖性，并得出总订单履行时间的均值和方差的近似分析表达式。我们通过内部详细流程模拟和外部方输出测量来验证分析表达式。然后，我们使用优化模型分析交付成本与服务质量的权衡，该模型通过 () 约束最小化预期订单履行成本，重点关注满足交付时间期限。优化模型确定了拣选员的数量、最佳交付批量大小以及交付客户订单所需的车辆数量。实现高交付可靠性是有代价的。与具有 DP 约束的模型相比，我们观察到从没有 DP 约束的模型获得的所有数据参数设置的平均预期订单履行成本降低了 8.9%；然而，订单履行时间的均值和标准差分别增加了44.1%和18.6%，导致交货可靠性较低。我们进一步证明，对订单履行流程的综合分析对于设定可靠的履行到期时间至关重要。