区域时变路网下的低碳冷链配送路径优化研究  

Low Carbon Distribution Path Optimization of Cold Chain Logistics Considering Regional Time-varying Velocity

作　　者：杨立君[1] 丁政罡 左大发 钟双喜 张驰[1] 石佳悦 YANG Lijun;DING Zhenggang;ZUO Dafa;ZHONG Shuangxi;ZHANG Chi;SHI Jiayue(Hubei University of Automotive Technology,Hubei Shiyan 442002,China)

机构地区：[1]湖北汽车工业学院,湖北十堰442002

出　　处：《包装工程》2025年第7期212-223,共12页Packaging Engineering

基　　金：国家社会科学基金一般项目(23BGL219)。

摘　　要：目的优化在区域时变路网下的生鲜冷链配送路径,降低企业的配送成本,提高配送效率。方法针对冷链配送中的时效性和温控管理要求,构建结合道路拥堵状况的区域时变车辆行驶函数,建立基于生鲜冷链配送成本的优化模型;研究采用改进的粒子群算法(PSO-GA)进行求解,并比较区域时变模型、时变模型、静态模型的优化结果。结果在求解精度和效率方面,PSO-GA均显著优于粒子群算法(PSO)和遗传算法(GA);在总配送成本方面,PSO-GA比PSO降低2.0%,比GA降低4.2%;在碳排放成本方面,PSO-GA比PSO降低3.9%,比GA降低11.2%。结论模型在区域复杂拥堵环境下成功降低配送成本和碳排放成本,能够较好地仿真现实道路交通配送现状,具有很好的实际意义。The work aims to optimize the cold chain distribution path of fresh food under the regional time-varying road network,to reduce the distribution cost of enterprises and improve the distribution efficiency.According to the timeliness and temperature management requirements of cold chain distribution,the regional time-varying vehicle travel function combined with road congestion was constructed,and the optimization model based on cold chain distribution cost of fresh food was established.The improved particle swarm optimization algorithm(PSO-GA)was used to solve the problem,and the optimization results of regional time-varying model,time-varying model and static model were compared.PSO-GA was superior to particle swarm optimization(PSO)and genetic algorithm(GA)in both accuracy and efficiency.In terms of total distribution cost,PSO-GA was 2.0%lower than PSO and 4.2%lower than GA.In terms of carbon emissions,PSO-GA was 3.9%lower than PSO and 11.2%lower than GA.The model can successfully reduce the distribution cost and carbon emission cost in the complex regional congestion environment,and can better simulate the reality of road traffic distribution,which has a good practical significance.

关 键 词：冷链物流 配送路径优化 时变速度 粒子群算法 碳排放 

分 类 号：F25[经济管理—国民经济] TP18[自动化与计算机技术—控制理论与控制工程]