系统管理学报

系统管理学报 ›› 2024, Vol. 33 ›› Issue (6): 1461-1470.DOI: 10.3969/j.issn.2097-4558.2024.06.006

• 工业工程与工程管理 • 上一篇    下一篇

新零售背景下卡车与无人机协同的电商物流末端配送优化

蒋丽1,2，王洪艳1,2，梁昌勇1,2   

  1. 1.合肥工业大学管理学院，合肥 230009；2.过程优化与智能决策教育部重点实验室，合肥 230009
  • 收稿日期:2023-04-23 修回日期:2023-07-12 出版日期:2024-11-28 发布日期:2024-12-03
  • 基金资助:

    教育部人文社会科学资助项目（23YJA630037，20YJC630007）；安徽省自然科学基金资助项目（2308085MG224）；安徽省创新战略与软科学研究重点项目（202206f01050017）；国家自然科学基金资助项目（72131006，72188101）；中央高校基本科研项目（JS2021ZSPY0037）

Optimization of E-Commerce Logistics Last Mile Distribution Based on Truck and Drone Collaboration in the New Retail Context

JIANG Li1,2, WANG Hongyan1,2, LIANG Changyong1,2   

  1. 1.School of Management, Hefei University of Technology, Hefei 230009, China; 2.Key Laboratory of Process Optimization and Intelligent Decision-Making of the Ministry of Education, Hefei 230009, China
  • Received:2023-04-23 Revised:2023-07-12 Online:2024-11-28 Published:2024-12-03

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摘要：

消费需求与用户体验是电商新业态的关注重点，电商物流作为其中重要的一环，在末端配送中仍以低成本为导向，消费者“门到门”配送需求没有得到完全满足。为更好地满足用户的上门配送需求、提升物流服务水平，在考虑无人机载重及飞行范围的条件下，提出一种卡车与无人机协同的配送路径规划问题。以卡车与无人机综合配送成本最小为目标建立混合整数规划模型，并提出一种改进混合蚁群算法对问题进行求解，实现卡车与无人机路径的联合优化。最后，通过算例实验验证了所建模型的合理性和设计算法的有效性，为提升电商物流末端配送服务水平提供决策参考和依据。

关键词:

新零售, 电商物流, 协同配送, 蚁群算法

Abstract:

Consumer demand and user experience are the key focuses of the new format of e-commerce. As an important part of e-commerce, last mile delivery is cost-oriented and has a low rate of door-to-door distribution. Consumers’ door-to-door distribution needs have not been fully met. To better meet users’ door-to-door service needs and improve logistics service, a collaborative distribution optimization problem involving trucks and drones is proposed, taking into account the load capacity and flight range of drones. In addition, a mixed integer programming model is formulated with the objective of minimizing the comprehensive distribution cost of trucks and drones. Moreover, an improved hybrid ant colony algorithm is proposed to solve the problem and schedule the route of trucks and drones. Furthermore, the rationality of the model and the effectiveness of the algorithm are verified through a series of experiments, providing decision-making reference and basis for improving the service level of e-commerce logistics in the last mile delivery.

Key words:

new retail, e-commerce logistics, collaborative distribution, ant colony algorithm

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