EXPRESS: Scaling Urban On-Demand Delivery: A Dabbawala-Inspired System for Handling Massive Demands via Public Transit

公共交通 过境(卫星) 交通系统 计算机科学 缩放比例 输送系统 业务 运输工程 按需 医学 数学 多媒体 几何学 工程类 药理学
作者
Yunqing Feng,Yiqi Sun,Wei Qi,Zuo‐Jun Max Shen
出处
期刊:Production and Operations Management [Wiley]
标识
DOI:10.1177/10591478251394130
摘要

With the rapid growth of omnichannel retailing and the takeaway delivery economy, the classic point-to-point mode for on-demand delivery is deficient in delivery capacity, coverage area, dispatching efficiency, and courier safety assurance. Inspired by the success of Dabbawala, a historical Indian company for lunch delivery, we propose a novel public on-demand delivery service system that uses the public transit network to satisfy stochastic delivery demands. In particular, the proposed system includes a radial public transit network for intermediate transshipment, as well as couriers with e-bikes for terminal pick-up and drop-off. Our research aims to generate system design that minimizes the sum of penalty costs from lost sales and operational costs associated with courier terminal delivery distance. Solving the integrated system optimization problem relies on incorporating operational details, especially the allocation strategies of the lines’ capacity and the couriers’ terminal traveling modes. For the former, we propose a novel flexible design, called dual long-chain design, to improve flexibility. For the latter, we propose an elegant approximation of optimal service region partitioning that minimizes the expected terminal delivery distance and the resulting costs, without compromising delivery timeliness. Leveraging the theoretical results of the operational strategies, we simplify the integrated optimization problem and propose an efficient approximation algorithm. Finally, we validate the advantage of the proposed system over classic point-to-point delivery in satisfying demands and reducing costs through extensive numerical experiments, providing managerial insights in handling massive on-demand delivery demands and utilizing the idle capacity of the public transit system.
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