Logistics Path Decision Optimization Method of Fresh Product Export Cold Chain Considering Transportation Risk

冷链 产品(数学) 层次分析法 路径(计算) 最短路径问题 计算机科学 遗传算法 构造(python库) 运筹学 供应链 决策模型 业务 数学 工程类 营销 机械工程 理论计算机科学 机器学习 图形 程序设计语言 几何学
作者
Lifu Chen,Zhifeng Shen
出处
期刊:Computational Intelligence and Neuroscience [Hindawi Publishing Corporation]
卷期号:2022: 1-11 被引量:7
标识
DOI:10.1155/2022/8924938
摘要

The cold chain logistics route of fresh product export is characterized by large quantity and complexity, which is prone to cause transportation risks of different degrees in the process of fresh product export transportation and affects the decision-making effect of the cold chain logistics route. Therefore, in order to improve the ability of cold chain logistics route planning and shorten the transportation time, an optimization method of fresh product export cold chain logistics route decision considering transportation risk was proposed. This paper analyzes the basic characteristics and classification of cold chain logistics by means of risk quantification and uses the K-nearest neighbor algorithm to predict the risk of traffic congestion, so as to shorten the transportation time. Ahp process is used to construct a risk factor judgment matrix and determine the index weight of risk factors, so as to reduce the error of path planning. A genetic algorithm is introduced to construct the optimal decision function of the cold chain logistics route of new product export and realize the optimization of cold chain logistics route decision of fresh product export. Experimental results show that the method presented in this paper can effectively improve the decision-making effect of cold chain logistics route and select the shortest and most smooth transportation path to complete logistics distribution. The decision-making accuracy of the route decision effect is 90%, and the transportation time is 31.45 min, which has certain feasibility and applicability.

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