摘要
运用贝叶斯网络对供应链中供应扰动风险的相关因素进行量化分析,得出了在供应扰动情况下以最短时间恢复正常生产是减少损失的最有效措施,而追加生产量不会大幅度降低损失.最后选择一个典型供应扰动案例,对基于贝叶斯网络的供应扰动风险态势进行算例分析,证明了模型的可行性和结论的合理性.
The paper uses the bayesian network to analyze the supply disturbance risk factors in the supply chain,arrives at a condusion that to resume normal production within shortertime is the most effective measure to reduce losses but it is not the case for the production in large scale. The authors selected atypical case of supply disturbances, analyzed the case based on the current risk situation on the Bayes Jan network,and proved its feasibility and reasonableness.
出处
《安徽工程大学学报》
CAS
2011年第4期81-84,共4页
Journal of Anhui Polytechnic University
基金
安徽省高校自然科学基金资助项目(kj2011a033)
关键词
供应扰动
风险
态势
贝叶斯网络
supply disturbances
risk
the current situation
Bayesian network
