城市配送中共享物流车辆调度优化模型及实证分析  

Optimization Model and Empirical Analysis of Shared Logistics Vehicle Scheduling in Urban Distribution

作　　者：施滢萍 SHI Yingping(West Yunnan University of Applied Sciences,Dali 671006,China)

机构地区：[1]滇西应用技术大学,云南大理671006

出　　处：《物流科技》2025年第6期67-70,共4页Logistics Sci Tech

基　　金：云南省教育厅科学研究基金项目“消费者视角下我国快递企业物流服务质量评价研究”(2023J1279)。

摘　　要：共享物流车辆调度在城市配送体系中具有关键作用。科学的调度模式优化能够显著提升配送效率,并有效削减运营成本。文章致力构建动态多目标路径规划模型,并以配送成本、时间与车辆装载率为优化目标,引入禁忌搜索算法进行路径迭代优化。以北京市城区共享物流数据为例的实证分析显示,优化模型减少了配送延误,提升了车辆装载率和配送准时率。该优化策略在复杂配送环境中展现了较高的实际应用价值,为城市物流系统的智能调度提供了重要理论支撑和实践指导。Shared logistics vehicle scheduling plays a critical role in urban distribution systems,and scientifically optimizing scheduling models can effectively enhance distribution efficiency and reduce operational costs.A dynamic multi-objective path planning model was developed,targeting distribution costs,time,and vehicle load rates as optimization objectives.The Tabu Search Algorithm was introduced to iteratively optimize paths.Empirical analysis,based on shared logistics data from urban areas in Beijing,demonstrated that the optimized model significantly reduced delivery delays while improving vehicle load rates and delivery punctuality.This optimization strategy shows high practical value in complex distribution environments,providing essential theoretical support and practical guidance for intelligent scheduling in urban logistics systems.

关 键 词：共享物流 车辆调度 动态路径规划 城市配送 

分 类 号：F259.2[经济管理—国民经济] U492.22[交通运输工程—交通运输规划与管理]