Reliability Analysis of Logistics Service Supply Chain System Based on Fuzzy Bayesian Networks

（Shenyang University of Technology，Shenyang，Liaoning110870，China）

研究[J].中国流通经济，2010，24（6）：27-30.

[17]HUANG H Z， ZUO M J ，SUN Z Q. Bayesian reliability analysis for fuzzy lifetime data[J].Fuzzy sets & systems， 2006，157（12）：1 674-1 686.

[18]HELGE L，LUIGI P. Bayesian networks in reliability[J].Re⁃ liability engineering and system safety，2007，92（1）：92108.

[19]PENG W， LI Y F MIJ ，et al. Reliability of complex sys⁃

， tems under dynamic conditions：a Bayesian multivariate degradation perspective[J].Reliability engineering & sys⁃ tem safety，2016，153（1）：75-87.

[20]BORSUK M E，STOW C A，RECKHOW K H. A Bayesian network of eutrophication models for synthesis，prediction， and uncertainty analysis[J].Ecological modelling，2004，173 （2-3）：219-239.

[21]JACKSON C，MOSLEH A. Bayesian inference with overlapping data： methodology for reliability estimation of multi- state on- demand systems[J].Journal of risk & reli⁃ ability，2012，226（3）：283-294. [22]张浩，张铁男，何明珂，等.基于多层Bayes

估计的战略协[J]. 2010，25同网络供应链可靠性研究 控制与决策，

（10）：1 552-1 556+1 566.

[23]LIU，W.H，XIE，D. Quality decision of the logistics service

supply chain with service quality guarantee[J].International

journal of production research，2013，51（5）：1 618-1 634. [24]董豆豆，冯静，孙权，等.模糊情形下基于贝叶斯网络的

可靠性分析方法[J].系统工程学报，2006（6）：668-672. [25]WILSON A G，HUXURBAZAR A V. Bayesian networks for multilevel system reliability[J].Reliability engine- ering & system safety，2007，92（10）：1 413-1 420.

[26]CAI B，LIU Y，LIU Z，et al. Using Bayesian networks in re⁃ liability evaluation for subsea blowout preventer control system[J].Reliability engineering & system safety，2012， 108（12）：32–41. [27]高志军，刘伟，高洁.服务主导逻辑下物流服务供应链的

价值共创机理[J].中国流通经济，2014，28（11）：71-77. [29]单宝玲.基于客户需求的供应链物流服务质量研究[J].中

国流通经济，2007，21（9）：26-28. [28]陈东宁，姚成玉.基于模糊贝叶斯网络的多态系统可靠性分析及在液压系统中的应用[J].机械工程学报，2012， 48（16）：175-183. [30]刘艳秋，蔡超.考虑可靠性的物流服务供应链的契约设

计[J].控制与决策，2017，32（11）：2 039-2 044. [31]冯向前，谭倩云，钱钢.犹豫模糊语言的可能度排序方法[J].控制与决策，2016，31（4）：640-646.

责任编辑：林英泽

Abstract：The authors put forward the method of multi- state system reliability analysis with the help of Fuzzy Bayesian Networks to solve the problem that it is difficult for complex logistic service supply chain to carry out reliability analysis while facing uncertain fuzzy information. Based on the fuzzy theory，the authors，first，analyze the status set and the fuzzy probability of changes in the status of different nodes in the logistic system，establish the fuzzy multi-state Bayesian network model for the supply chain based on the theory of failure tree model，and describe the probability of status change，and the uncertain relation among different status in logistic units with the help of triangular fuzzy number；second，with the use of optimization algorithm， they compute the reliability of the multi- state logistic system，the fuzzy probability of changes in status，and the posterior probability of certain breakdown in nodes with changes in system status，and make out the importance of logistic nodes and its status with the help of system importance analysis；and third，they testify the suitability and efficiency of this method in multistate logistic system reliability analysis with the use of samples. It is found that this method can fully handle the uncertain fuzzy information，improve the efficiency of reliability analysis，and provide logistic service enterprises with theoretical and data support in improving the weak links having impact on reliability.

Key words：Fuzzy Bayesian Network；logistics service supply chain system；multi- state system；uncertainty；reliability