Reliability Analysis And Optimization Of Cold Chain Distribution System For Fresh Agricultural Products

In recent years,with the government's emphasis on the development of the cold chain logistics market for fresh agricultural products,the rapid development of agricultural cold chain logistics has been promoted in many aspects.At the same time,as the income level of residents increases,the freshness requirements for fresh agricultural products are getting higher and higher.However,in the actual circulation of fresh agricultural products,there is still a serious problem of “broken chain” phenomenon of cold chain logistics and the fresh agricultural product has a high corrosion rate.Therefore,how to improve the reliability of cold chain distribution and reduce the corrosion rate is the main problem that needs to be solved in the fresh cold chain logistics industry.This paper takes the cold chain logistics distribution system of fresh agricultural products as the research object.Firstly,by analyzing the characteristics of each process in the cold chain distribution system,the uncertain factors which affect the distribution efficiency are found out.Then,the fault tree model of cold chain distribution system is constructed from three aspects: delivery delay,quantity and variety inadequacy and unqualified products,which could intuitively show the logical relationship between the influencing factors.In order to facilitate the reasoning,the fault tree model is then transformed into a Bayesian network of the cold chain distribution system failure to assess the reliability of the system.Since the actual data is difficult to obtain,the prior probability of each influencing factor and the conditional probability table of some intermediate nodes are obtained by the fuzzy comprehensive evaluation method,while the logic gate of the fault tree corresponds to the conditional probability table of other intermediate nodes.The reliability of the cold chain distribution system is evaluated by calculating the probability of the system working normally.The Bayesian network can realize:(1)Find out the main factors that cause the failure of the cold chain distribution system by calculating the posterior probability of each influencing factor;(2)Find out the key factors influencing the reliability of the cold chain distribution system by calculating the probability importance of each factor;(3)Find out the factors that have a great impact on the cold chain distribution system through sensitivity analysis.The feasibility of the reliability analysis of cold chain distribution of fresh produce based on Bayesian network is verified by a case study.According to the analysis,it shows that the probability importance is more suitable as a basis for identifying the factors affecting the reliability of the cold chain distribution system.Since the optimization of reliability is usually limited by cost,this paper takes the lowest reliability cost as the optimization object,and uses the expected system reliability index as the constraint condition.Combining the feasibility and probability importance of each influencing factor,the nonlinear programming model is constructed.By allocating the reliability of each influencing factor,the reliability of the cold chain distribution system is improved,and the purpose of optimizing the cold chain distribution process is achieved.The validity of the model is verified by a case study.The optimization result shows that higher reliability assigned to factors with high probability importance is more conducive to the improvement of system reliability.According to the optimization results,corresponding improvement suggestions are proposed.