Operations Research and Management Science ›› 2026, Vol. 35 ›› Issue (2): 27-33.DOI: 10.12005/orms.2026.0038

• Theory Analysis and Methodology Study • Previous Articles     Next Articles

Research on Crowdsourcing Collaborative Delivery Solutions toInstant Delivery in Delivery-challenged Areas

WANG Xinxin1,2, ZHANG Zelong2, REN Liang1,2, ZANG Shuowen2   

  1. 1. Institute of Service Science and Engineering, Wuhan University of Science and Technology, Wuhan 430065, China;
    2. School of Management, Wuhan University of Science and Technology, Wuhan 430065, China
  • Received:2024-09-23 Online:2026-02-25 Published:2026-07-08

即时配送下面向交付困难区域的众包协同配送研究

王鑫鑫1,2, 张泽龙2, 任亮1,2, 臧硕文2   

  1. 1.武汉科技大学 服务科学与工程研究中心,湖北 武汉 430065;
    2.武汉科技大学 管理学院,湖北 武汉 430065
  • 通讯作者: 王鑫鑫(1980-),男,湖北十堰人,教授,博士,研究方向:数字经济,智慧物流。Email: wangxinxin@wust.edu.cn。
  • 基金资助:
    武汉市交通强国建设试点科技联合项目(2025-2-4);武汉科技大学服务科学与工程研究中心开放基金重点项目(2025ISSEA06)

Abstract: In recent years, with the rapid economic development of China and the further deployment of take-out services and new retail, consumers’ differentiated demands for instant delivery have driven the diversified development of the service business categories. The door-to-door delivery service and high-quality performance capabilities of instant delivery have greatly met consumers’ diverse needs for convenience, timeliness, and other aspects, enabling instant delivery services to further expand to all-time, all-scenario, and all-distance coverage. Although instant delivery is in a golden period of development, some areas still face issues that have not been properly addressed due to their unique regulatory environments. These areas often become “blind spots” and “difficult points” in the process of instant delivery operation and management. Therefore, this paper collectively refers to such areas as “delivery-challenged regions,” characterized by two types of issues: one involves areas where riders do not have permission to enter due to special regulations, requiring customers to pick up their orders at the perimeter, such as university campuses with access control and residential communities with special property management systems; the other involves areas where riders can enter but face challenges in door-to-door delivery due to the compact arrangement of buildings and high population density, necessitating local area knowledge to ensure timely delivery, such as business districts with concentrated office buildings and industrial parks. The differentiated regional regulatory environments result in weakened delivery timeliness for traditional riders in delivery-challenged regions, and in some cases, riders are unable to complete door-to-door delivery services, leading to customer dissatisfaction and reduced rider willingness to deliver. This poses significant challenges to logistics service providers in planning delivery schemes.
To address the issues in delivery-challenged regions, this paper proposes a collaborative delivery solution combining dedicated riders and crowdsourced riders. A mixed-integer programming model is established with the objective of minimizing the sum of vehicle travel costs, crowdsourced rider recruitment compensation costs, and time window violation penalty costs. Upon receiving a batch of orders with their locations and flexible time windows, the delivery platform determines the delivery tasks for dedicated and crowdsourced riders, the number of crowdsourced riders to recruit, and their respective delivery routes, enabling the two types of riders to collaboratively complete the delivery tasks. An improved variable neighborhood search algorithm is designed based on scenario characteristics, using a greedy algorithm to generate initial solutions to open vehicle routing within the region and closed vehicle routing outside the region. Local search operators are then designed based on three optimization stages: closed vehicle routing optimization outside the region, open vehicle routing optimization within the region, and interactive optimization of vehicle routing inside and outside the region, to enhance the algorithm’s global optimal search capability.
Finally, the case studies are conducted to verify the effectiveness and applicability of the model and algorithm. The results indicate that the crowdsourced collaborative delivery solution for instant delivery in delivery-challenged regions can effectively reduce total delivery costs, providing a valuable reference for improving service quality in future instant delivery operation and management.

Key words: instant delivery, delivery-challenged areas, crowdsourcing collaborative delivery, variable neighborhood search algorithm

摘要: 随着消费者需求的显著分化,即时配送业务品类迎来了多元化发展,其送货上门服务和优质履约能力已成为消费者选择即时配送的重要因素。即时配送为消费者提供了极大便利性和时效性的同时,仍有部分区域的配送受到自身特殊的规则环境限制,导致区域内出现履约时效性不强、无法送货上门等配送服务质量不高的现象,令消费者不满的同时降低了骑手的配送意愿。本文将此类具有特殊规则环境的区域统称为“交付困难区域”,针对交付困难区域特征提出一种众包协同配送方案,以车辆行驶成本、招募众包补偿成本和违反时间窗惩罚成本之和最小化为目标建立了混合整数规划模型,基于场景特征设计改进的变邻域搜索算法求解模型。最后,通过算例分析验证模型与算法的有效性和适用性,结果表明,即时配送下面向交付困难区域的众包协同配送方案能够有效降低配送总成本,为未来即时配送运营管理中服务质量提升提供有效参考。

关键词: 即时配送, 交付困难区域, 众包协同配送, 变邻域搜索算法

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