基于微枢纽的三方外卖配送服务中转运输分析
Analysis of Transshipment in Three-Sided Meal Delivery Services via Microhubs
AI总结：
本文提出一种基于中心微枢纽的外卖配送中转运输策略，通过划分服务区域并利用网络化G/G/m队列建模分析。研究发现，在高需求或低供给条件下该策略能显著降低顾客等待时间和车辆行驶里程，美团外卖数据验证了其在高峰时段和繁忙区域的有效性。
摘要：
本文介绍并分析了一种新颖的外卖配送中转运输策略。在该方法中，服务区域被划分为较小的子区域，配送员被分配专门在这些子区域内运作。同时，一个位于中心的微枢纽作为物流集散点，以促进外卖包裹向不同子区域的集货与转运。我们使用网络化G/G/m队列对带有中转运输的外卖配送系统进行建模，并解析近似两个关键系统性能指标——顾客等待时间和车辆行驶里程——以评估所提策略的有效性。中转运输实现的性能与不带中转运输的经典取送策略的性能进行了基准比较，两者均使用连续近似进行预测。对于后者，我们通过纳入单个订单的配送距离特征来增强现有建模，以更好地匹配外卖配送场景。我们的比较表明，在高需求或低供给条件下，通过中转运输进行外卖配送在两项指标上均优于无中转运输的基准，在服务更大区域或处理长途订单方面具有特别的优势。这一结论得到了使用美团外卖经验数据的数值实验的证实，该实验表明，最优配置的中转运输策略可以在午餐高峰时段和最繁忙的街区显著改善顾客和配送员的服务性能。虽然中转运输在非高峰时段继续减少配送员的车辆行驶里程，但随着需求减少，与无中转运输的基准相比，它会导致更长的顾客等待时间。
英文摘要：
This paper introduces and analyzes a novel transshipment strategy for meal delivery. In this approach, the service area is partitioned into smaller sub-areas, with deliverers assigned to operate exclusively within these sub-areas. Meanwhile, a centrally located microhub functions as a logistic depot to facilitate the batching and transfer of meal packages toward different sub-areas. We model the meal delivery system with transshipment using networked G/G/m queues and analytically approximate two critical system performance metrics -- customer waiting time and vehicle miles traveled -- to evaluate the effectiveness of the proposed strategy. The performance achieved by transshipment is benchmarked against that of the classic pickup-and-delivery strategy without transshipment, both predicted using continuous approximations. For the latter, we enhance the existing modeling by incorporating the delivery distance profiles of individual orders to better match the meal delivery context. Our comparisons indicate that meal delivery via transshipment outperforms the non-transshipping counterpart across both metrics under either high-demand or low-supply conditions, with particular advantages in servicing larger areas or handling long-distance orders. This conclusion is corroborated by a numerical experiment using empirical meal delivery data from Meituan, which suggests that an optimally configured transshipment strategy can significantly improve service performance for both customers and deliverers during peak lunch hours and in the busiest districts. While transshipment continues to reduce vehicle miles traveled by deliverers during non-peak hours, it results in longer customer waiting times compared to the benchmark without transshipment as demand decreases.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
