Research On Risk Evaluation Of Cold Chain Logistics Distribution System Based On Entropy Weighted TOPSIS And Fuzzy Bayesian Network

With the improvement of material living standard,people's demand for fresh products is increasing,such as fresh milk,fish,fruits and vegetables.However,fresh goods are not easy to preserve and easy to damage and deteriorate,so it is necessary to keep them fresh at low temperature in the logistics to reduce the loss and deterioration,so cold chain logistics came into being.Distribution is the last link of cold chain logistics,also known as "the last kilometer" distribution,which has become the most critical link of cold chain logistics distribution.In this process,if there is a problem in product quality,it will directly affect customer satisfaction.Therefore,through scientific and effective methods to identify the risk factors in the distribution process,and risk assessment of the whole distribution system,we can control and prevent the risk,improve the freshness of food,which is of great significance to the operation of cold flow logistics.In this paper,cold chain logistics distribution as the starting point,through theoretical modeling,questionnaire survey and other methods to study the risk assessment and control of cold chain logistics distribution system,the main work is as follows:(1)Analysis of risk factors in the process of cold chain logistics distributionAccording to the process of cold chain logistics distribution,using the system analysis thought of "human machine environment management",this paper divides the risk influencing factors into four aspects of "human machine environment management",comprehensively analyzes the influencing factors in all aspects,and abstracts 30 typical factors affecting cold chain logistics distribution,such as operation risk and management risk.(2)Selection of risk factors of cold chain logistics distribution based on entropy weighted TOPSISBased on the analysis of risk factors,aiming at the problem that the risk factors in distribution are difficult to identify,the entropy weighted TOPSIS method combined with questionnaire survey is used to select 15 influencing factors with higher risk degree by comparing the importance of many risk factors,so as to build the risk evaluation index system of cold chain logistics distribution.(3)Risk evaluation model of cold chain logistics distribution system based on Fuzzy Bayesian networkAccording to the causality,the risk evaluation index system is transformed into the Bayesian network structure,and the variable value range is given.At the same time,the fuzzy number theory is introduced to determine the probability value of the root node of the Bayesian network,and the algorithm of non root node condition probability is studied and improved in combination with the actual situation,and then the risk evaluation model of the cold chain logistics distribution system is constructed.(4)Take Shuang Hui cold chain logistics company as an example to evaluate and control the risk of cold chain logistics distributionTaking Shuang Hui cold chain logistics company as an example,the risk level and risk impact degree of cold chain logistics distribution in Shuang Hui cold chain logistics company are obtained.Based on this,the operation of distribution link is improved to avoid commodity loss to the greatest extent.The result of the risk assessment is consistent with the actual situation,which verifies the rationality and practicability of the model.The research content of this paper not only makes the cold chain logistics enterprises reduce the economic loss caused by the distribution risk and improve the distribution efficiency,but also provides the decision-making basis for the risk control of the end link distribution and improves the security management decision-making ability of the distribution system,which proves that the research results of this paper have practical value and practical significance.