生鲜冷链物流配送多车型动态车辆路径优化  

Multi-model Dynamic Vehicle Routing Optimization of Fresh Cold Chain Logistics Distribution Under Green Logistics

作　　者：宾厚[1] 徐晶晶 王素杰 刘妃 BIN Hou;XU Jingjing;WANG Sujie;LIU Fei(School of Economics and Management,Hunan University of Technology,Zhuzhou,Hunan 412007)

机构地区：[1]湖南工业大学经济与管理学院,湖南株洲412007

出　　处：《管理现代化》2025年第1期182-191,共10页Modernization of Management

基　　金：国家社会科学基金项目“乡村振兴战略下县、乡、村三级农村物流协同机制研究”(19BGL177);2024年湖南省研究生科研创新项目“考虑动态需求的生鲜农产品冷链物流共同配送路径优化研究”(CX20240907);2025年湖南省社会科学成果评审委员会立项课题“低空物流视域下湖南省‘县乡村车机协同’配送模式及策略研究”(XSP25YBZ181)。

摘　　要：针对绿色物流下生鲜冷链物流配送动态车辆路径优化问题,将研究过程分为预优化和动态调整两阶段,以总成本最低为目标函数构建模型,分别采用K-means聚类算法、改进遗传算法和插入式算法对模型进行求解。结果表明:多车型配送比单独使用三种不同型号车型在配送总成本上分别降低3.98%、5.87%和10.06%,更具成本优势;与传统遗传算法相比,本文提出的改进遗传算法在各项配送成本求解上均更优,配送总成本降低7.74%,且能较快求得最优解,验证了算法的有效性。Aiming at the dynamic vehicle routing optimization problem of fresh cold chain logistics distribution under green logistics,the research process is divided into two stages:pre-optimization and dynamic adjustment.The model is constructed with the lowest total cost as the objective function.K-means clustering algorithm,improved genetic algorithm and plug-in algorithm are used to solve the model respectively.The results show that the total cost of multi-vehicle distribution is reduced by 3.98%,5.87%and 10.06%,respectively,compared with using three different models alone.Compared with the traditional genetic algorithm,the improved genetic algorithm proposed in this paper is better in solving the distribution cost,the total distribution cost is reduced by 7.74%,and the optimal solution can be obtained quickly,which verifies the effectiveness of the algorithm.

关 键 词：车辆路径 生鲜冷链 绿色物流 改进遗传算法 

分 类 号：F253.4[经济管理—国民经济] U116[交通运输工程]