管理评论

管理评论 ›› 2023, Vol. 35 ›› Issue (3): 267-281.

• 物流与供应链管理 • 上一篇    下一篇

“互联网+”预约平台下动态取件路径优化研究

马艳芳1, 杨帆1, 周晓阳2, 康凯1, 李宗敏3   

  1. 1. 河北工业大学经济管理学院, 天津 300401;
    2. 西安交通大学管理学院, 西安 710049;
    3. 四川大学商学院, 成都 610065
  • 收稿日期:2021-01-25 出版日期:2023-03-28 发布日期:2023-04-28
  • 通讯作者: 周晓阳（通讯作者），西安交通大学管理学院教授，博士生导师，博士。
  • 作者简介:马艳芳，河北工业大学经济管理学院副教授，硕士生导师，博士；杨帆，河北工业大学经济管理学院硕士研究生；康凯，河北工业大学经济管理学院教授，博士生导师，博士；李宗敏，四川大学商学院教授，硕士生导师，博士。
  • 基金资助:
    国家自然科学基金项目(72202056；71871175；72174134)；河北省自然科学基金青年项目(G2020202008)；四川省哲学社会科学规划项目(SC22EZD048)。

Dynamic Routing Optimization for Home Pick-up Service under ‘Internet+’ Appointment Platform

Ma Yanfang1, Yang Fan1, Zhou Xiaoyang2, Kang Kai1, Li Zongmin3   

  1. 1. School of Economics and Management, Hebei University of Technology, Tianjin 300401;
    2. The School of Management, Xi'an Jiaotong University, Xi'an 710049;
    3. Business School, Sichuan University, Chengdu 610065
  • Received:2021-01-25 Online:2023-03-28 Published:2023-04-28

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摘要： 互联网技术的飞速发展，极大提高了预约取件服务水平，其竞争也空前激烈。针对预约取件中运输成本高、客户满意度低等问题，结合实际运营情况，考虑客户模糊时间窗，以总运输成本最低为目标，构建“互联网+”预约平台下动态取件路径模型。提出动态遗传算法求解，其中设计节约里程和贪婪插入的初始化编码，采用最小成本交叉操作、自适应交叉率及精英保留策略。基于Taillard、Christophides和Fisher等21个经典基准案例，与其他四种算法对比，改进算法得到15个更好的解，表明其良好的收敛性。最后，对模拟天津实际案例的结果分析和灵敏度分析，验证模型的有效性和适用性，为快递企业上门取件服务提供有力的决策支持。

关键词: 互联网+, 预约平台, 上门取件, 动态路径, 遗传算法

Abstract: The rapid development of the internet technology has greatly improved the service level of home pick-up in express industry, which also resulted in an unprecedented fierce competition. Considering high cost and low customer satisfaction in the process of home pick-up service, a dynamic routing problem model is proposed for home pick-up service based on the internet appointment platform. In this model, customers’ time windows are considered as fuzzy variables, and minimizing the total cost is taken as the goal. Then, a dynamic scheduling-based genetic algorithm (GA) is proposed to solve the model, in which initial coding based on the Clarke and Wright savings algorithm or the greedy insertion is designed, and a best-cost route crossover and an elite retention strategy are adopted. Based on the 21 classic benchmarks composed of Taillard, Christophides and Fisher, a comparative analysis is performed with other four published algorithms to evaluate the performance of the improved GA. The results show that the improved algorithm obtains 15 better solutions and has good convergence. Finally, based on the result analysis and sensitivity analysis about a simulation case of an express company in Tianjin, the validity and applicability of the model are verified, which provides strong decision support for home pick-up service.

Key words: ‘Internet+’, appointment platform, home pick-up service, dynamic routing, genetic algorithm