刘静,王勇,阳静.考虑动态新增订单需求的快递物流即时配送优化方法研究[J].包装工程,2025,(5):197-208.
LIU Jing,WANG Yong,YANG Jing.On-demand Delivery Optimization Methods for Express Logistics Services Considering Dynamic New Order Demands[J].Packaging Engineering,2025,(5):197-208. |
| 考虑动态新增订单需求的快递物流即时配送优化方法研究 |
| On-demand Delivery Optimization Methods for Express Logistics Services Considering Dynamic New Order Demands |
| 投稿时间：2024-12-26 |
| DOI：10.19554/j.cnki.1001-3563.2025.05.025 |
| 中文关键词: 动态新增订单需求 即时配送 时间窗指派 改进的多目标蚁群优化算法 帕累托优化解 |
| 英文关键词: dynamic new order demands on-demand delivery time window assignment improved multi-objective ant colony optimization algorithm Pareto optimization |
| 基金项目:国家自然科学基金(72371044);重庆市教委科学技术研究重大项目(KJZD-M202300704);巴渝学者青年项目(YS2021058) |
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| 中文摘要: |
| 目的 针对传统快递物流即时配送中存在难以准时服务动态客户和配送时效性差等问题，提出动态订单插入策略和时间窗指派策略，研究考虑动态新增订单需求的快递物流即时配送优化问题。方法 首先，结合快递物流即时配送网络的周期性需求和新增订单需求，构建以物流运营成本最小和车辆使用数目最少的双目标车辆路径优化模型。其次，设计改进的多目标蚁群优化算法求解优化模型，该算法通过局部优化策略和外部档案更新机制来增强帕累托优化解的求解质量，进而提出动态订单插入策略和时间窗指派策略，进一步提升算法的整体搜索性能。再次，将改进的多目标蚁群优化算法与多目标粒子群算法、多目标灰狼优化算法和多目标多元宇宙优化算法进行对比分析，验证了提出算法的有效性。最后，结合重庆市某快递物流即时配送网络进行实例优化研究，并分析探讨了不同服务时间段的划分对物流运营成本、车辆使用数目和惩罚成本等指标的影响。结果 优化后的物流运营成本下降48%，车辆使用数目减少12辆，将配送中心服务时间分为3个时间段的优化方案效果最好。结论 提出的模型和算法有助于降低物流运营成本并减少配送车辆的使用数目，为考虑动态新增订单需求的快递物流即时配送优化提供方法支持和决策参考。 |
| 英文摘要: |
| The work aims to propose a dynamic order insertion strategy and a time window assignment strategy to study the optimization problem of express logistics on-demand delivery considering dynamic new order demands, so as to solve problems of difficulty in providing timely services to dynamic customers and poor delivery timeliness in traditional express logistics on-demand delivery. Firstly, a bi-objective vehicle routing optimization model was constructed to minimize the logistics operation cost and the number of vehicles used, considering the periodic demand of the express logistics on-demand delivery network and the new order demand. Secondly, an improved multi-objective ant colony algorithm was designed to solve the optimization model. This algorithm enhanced the quality of Pareto optimal solutions through local optimization strategies and external archive update mechanisms. And a dynamic order insertion strategy and a time window assignment strategy was further proposed to improve the overall search performance of the algorithm. Thirdly, the improved multi-objective ant colony algorithm was compared and analyzed with the multi-objective particle swarm optimization algorithm, the multi-objective grey wolf algorithm, and the multi-objective multi-verse algorithm, verifying the effectiveness of the proposed algorithm. Finally, an instance optimization study was conducted based on a certain express logistics on-demand delivery network in Chongqing, and the impact of different service time period divisions on indicators such as logistics operation cost, and the number of vehicles used, and penalty cost were analyzed and discussed. The results showed that the logistics operation cost was reduced by 48% after optimization, and the number of vehicles used was reduced by 12. The optimization scheme that divided the service time of the distribution center into three time periods had the best effect. In conclusion, the model and algorithm proposed in this paper are helpful to reduce the logistics operation cost and the number of vehicles used, providing method support and decision-making reference for the optimization of express logistics on-demand delivery considering dynamic new order demands. |
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