考虑交付失败的快递末端配送路径优化研究
Research on Optimization of Last-Mile Delivery Routes Considering Delivery Failure
摘要: 针对快递服务网络路径优化问题，因其存在高价值或面交的快递包裹，为了降低顾客投诉率并完成配送服务，需要额外规划二次配送路径。对此，考虑交付失败概率，以车辆固定成本、时间窗惩罚成本、一次配送成本以及二次配送成本之和为目标函数，构建多车型、有时间窗的快递末端配送路径优化模型，结合局部搜索策略对鸽群算法进行改进，并采用该算法进行求解，最终选择2辆车型A和2辆车型B，完成配送任务比基础鸽群算法降低成本约13.7%，验证了模型和算法的可行性，为快递服务网络优化提供参考性建议。
Abstract: Aiming at the express delivery service network route optimization problem, which involves high-value or hand-delivery parcels, additional secondary delivery routes need to be planned to reduce customer complaint rates and ensure successful delivery. Considering the probability of delivery failure, an optimization model for last-mile delivery with multiple vehicle types and time windows is constructed, with the objective function comprising fixed vehicle costs, time window penalty costs, primary delivery costs, and secondary delivery costs. By integrating a local search strategy, an improved Pigeon-Inspired Optimization (IPIO) algorithm is proposed and applied to solve the model. The solution ultimately selects 2 Type A vehicles and 2 Type B vehicles, reducing the total cost by approximately 13.7% compared to the basic PIO algorithm. This validates the feasibility of the model and algorithm, providing valuable insights for optimizing express service networks.
文章引用：米峰南. 考虑交付失败的快递末端配送路径优化研究[J]. 建模与仿真, 2025, 14(10): 168-181. https://doi.org/10.12677/mos.2025.1410615

参考文献

[1] 姬杨蓓蓓, 储昊, 成枫. 基于两阶段算法的快递企业末端配送网络优化研究[J]. 系统工程, 2019, 37(2): 100-105.
[2] Chen, R.M., Shen, Y.M. and Hong, W.Z. (2019) Neural-Like Encoding Particle Swarm Optimization for Periodic Vehicle Routing Problems. Expert Systems with Applications, 138, Article 112833. [Google Scholar] [CrossRef] 
[3] Vaziri, S.H., Etebari, F. and Vahdani, B. (2019) Development and Optimization of a Horizontal Carrier Collaboration Vehicle Routing Model with Multi-Commodity Request Allocation. Journal of Cleaner Production, 224, 492-505. [Google Scholar] [CrossRef] 
[4] Jabalameli, M.S., Barzinpour, F., Saboury, A. and Nasab, N.G. (2012) A Simulated Annealing-Based Heuristic for the Single Allocation Maximal Covering Hub Location Problem. International Journal of Metaheuristics, 2, 15-37. [Google Scholar] [CrossRef] 
[5] Li, Y., Soleimani, H. and Zohal, M. (2019) An Improved Ant Colony Optimization Algorithm for the Multi-Depot Green Vehicle Routing Problem with Multiple Objectives. Journal of Cleaner Production, 227, 1161-1172. [Google Scholar] [CrossRef] 
[6] Kim, D., Barnhart, C., Ware, K., et al. (1999) Multimodal Express Package Delivery: A Service Network Design Application. Transportation Science, 33, 341-428. https://pubsonline.informs.org/doi/abs/10.1287/trsc.33.4.391 [Google Scholar] [CrossRef] 
[7] Hu, W., Dong, J., Yang, K., Hwang, B., Ren, R. and Chen, Z. (2023) Reliable Design of Urban Surface-Underground Integrated Logistics System Network with Stochastic Demand and Social-Environmental Concern. Computers & Industrial Engineering, 181, Article 109331. [Google Scholar] [CrossRef] 
[8] 邓学平, 孙芹, 田帅辉. 基于不同车型的城市快递配送车辆路径优化研究[J]. 价值工程, 2020, 39(12): 275-280.
[9] 张梦颖, 秦进, 梁樑. 包含随机客户的选择性旅行商问题建模及求解[J]. 运筹与管理, 2018, 27(5): 8-14.
[10] 周林, 林云, 王旭, 等. 网购城市配送多容量终端选址与多车型路径集成优化[J]. 计算机集成制造系统, 2016, 22(4): 1139-1147.
[11] 许闯来, 胡坚堃, 黄有方. 不确定需求下快递配送网络鲁棒优化[J]. 计算机工程与应用, 2020, 56(3): 272-278.
[12] 江海, 陈峰. 面向快递同城运输的车辆路径问题研究[J]. 工业工程, 2019, 22(4): 58-63.
[13] Wei, L., Chen, Y., Guo, D., Ji, J., Chen, Z. and Zhuo, C. (2024) A Last-Mile Delivery System for Underground Logistics with “Self-Pickup+” and “Home-Entry+” Modes. Tunnelling and Underground Space Technology, 147, Article 105678. [Google Scholar] [CrossRef] 
[14] Zhao, L., Zhou, J., Li, H., Yang, P. and Zhou, L. (2021) Optimizing the Design of an Intra-City Metro Logistics System Based on a Hub-and-Spoke Network Model. Tunnelling and Underground Space Technology, 116, Article 104086. [Google Scholar] [CrossRef] 

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