交通运输系统工程与信息 ›› 2026, Vol. 26 ›› Issue (5): 68-78.DOI: 10.16097/j.cnki.1009-6744.2026.05.006

• 青年基金项目成果 • 上一篇    下一篇

需求响应式货运公交与众包骑手协同取货动态调度

姜晓红,华晶雯,王朵* ,李家伟,李仲恺   

  1. 南京林业大学,汽车与交通工程学院,南京210037
  • 收稿日期:2026-05-09 修回日期:2026-06-25 接受日期:2026-07-10 出版日期:2026-10-25 发布日期:2026-10-21
  • 作者简介:姜晓红(1985— ),女,江苏常州人,副教授。
  • 基金资助:
    国家自然科学基金青年科学基金 (52501144)。

Dynamic Joint Pickup Scheduling of Demand-Responsive Freight Transit and Crowdsourced Riders

JIANG Xiaohong, HUA Jingwen, WANG Duo*, LI Jiawei, LI Zhongkai   

  1. College of Automobile and Traffic Engineering, Nanjing Forest University, Nanjing 210037, China
  • Received:2026-05-09 Revised:2026-06-25 Accepted:2026-07-10 Online:2026-10-25 Published:2026-10-21
  • Supported by:
    Young Scientists Fund of the National Natural Science Foundation of China (52501144)。

摘要: 为扩展农村地区即时零售服务范围,并提高时效性,本文提出一种需求响应式货运公交与众包骑手协同的取货策略,订单统一配送至城乡公交客货邮融合首末站,由城乡公交完成末端配送,实现半日达。首先,依据订单空间分布设置偏移距离阈值,将零散订单分配给骑手,货运公交专注高密度区域,减少绕行;其次,引入订单中转合并策略,利用固定站点作为中转节点,将多车任务整合至单车完成,避免空驶返程;然后,以取货总成本最低为目标,构建两阶段调度模型,并设计遗传-变邻域搜索算法(GA-VNS)求解;最后,以南京市江宁东山片区为例,进行小、中、大规模订单实例验证。结果表明:大规模订单下,协同取货模式相较单一取货模式成本降低7.6%,行驶距离减少12.2%,效果显著;中转合并策略适用于农村即时零售发展初期,小规模订单下能提升32%满载率,减少返程空驶;自适应调整送达时间窗与分批处理时间间隔能有效平衡时效性与运营成本。

关键词: 物流工程, 协同取货, 动态调度, 货运公交, 需求响应, 众包骑手

Abstract: To extend the service scope of instant retail in rural areas and improve timeliness, this paper proposes a collaborative pickup strategy which integrates demand-responsive freight buses and crowdsourced couriers. Orders are uniformly delivered to the urban-rural bus passenger-freight-mail integration terminals, where the urban-rural buses perform the last-mile delivery to achieve half-day delivery. First, an offset distance threshold is set based on the spatial distribution of orders to assign scattered orders to couriers, while the freight buses focus on high-density areas to reduce detours. Second, an order transshipment consolidation strategy is introduced, using fixed stops as transfer nodes to consolidate multi-vehicle tasks into a single vehicle, thereby avoiding empty backhauls. Third, a two-stage scheduling model is formulated with the objective of minimizing total pickup cost, and is solved by a genetic algorithm with variable neighborhood search (GA-VNS). Finally, a case study is conducted in the Dongshan area of Jiangning District, Nanjing, with small, medium, and large order scales. The results show that under the large-scale orders, the collaborative pickup mode reduces the total cost by 7.6% and travel distance by 12.2% compared with the single pickup mode, demonstrating significant effectiveness. The transshipment consolidation strategy is particularly suitable for the early stages of rural instant retail development: under the small-scale orders, it increases the load factor by 32% and reduces empty backhaul trips. The adaptive adjustment of delivery time windows and batching intervals can effectively balance the timeliness and operational costs.

Key words: logistics engineering, collaborative pickup, dynamic scheduling, freight bus, demand response, crowdsourced couriers

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