模糊随机环境下基于风险传播视角的供应链脆弱性评估与治理

The complex and uncertain environment and the propagation of risk disturbances among the members of a supply chain are two key drivers of the supply chain vulnerability. Due to the presence of various types of uncertain factors, the real-life supply chain management activities are usually influenced by two-fold uncertainties where randomness and fuzziness coexist. Therefore, this project introduces fuzzy random theory into the study of supply chain vulnerability, and analyzes it from the perspective of risk propagation in supply chain network. It is to be anticipated that the law and internal mechanism of risk propagation in supply chain in fuzzy random environments can be well understudied via this study, and consequently, a theoretical basis for the assessment and governance of supply chain vulnerability in a scientific and effective way can be proposed, The study will take the supply risk in automobile supply chain for instance, and be conducted from the following three aspects: 1) the modelling of risk propagation in supply chain in fuzzy random environments; 2) the assessment of supply chain vulnerability based on the fuzzy random risk propagation model; 3 ) the strategy design for the improvement of supply chain vulnerability with cost constraints. In order to develop an effective analysis framework and methodologies for the assessment and governance of the supply chain vulnerability in fuzzy random environments, some key scientific problems, including the characterization and description of supply chain risk in fuzzy random environments, the arithmetic operation and simulation of fuzzy random variables, and the solving method of fuzzy random programming models, are to be thoroughly studied as well.

复杂多变的不确定环境和风险扰动在供应链成员企业间的传播是供应链脆弱性的两个关键驱动因素。由于各类不确定因素的存在，现实的供应链管理活动通常受到随机与模糊共存的双重不确定性的影响。因此，本项目将模糊随机理论引入到供应链脆弱性研究中，并从供应链网络风险传播的视角进行分析，期望能够为我们认识和理解模糊随机环境下供应链风险传播的运行规律和内在机理，进而科学有效地对供应链脆弱性进行评估与治理提供理论基础。具体研究将以汽车供应链中的供应风险为例从以下三个方面展开：1）模糊随机环境下的供应链风险传播建模；2）基于模糊随机风险传播模型的供应链脆弱性评估；3）考虑成本约束的供应链脆弱性改善策略设计。并对模糊随机环境下供应链风险的刻画与描述、模糊随机变量的运算及模拟、模糊随机规划模型的求解等关键科学问题进行深入研究，探索为模糊随机环境下的供应链脆弱性评估与治理构建一套科学合理的分析框架和方法。

复杂多变的不确定环境和风险扰动在供应链中的传播是供应链脆弱性的两个关键驱动因素。针对模糊随机环境下的供应链脆弱性评估与治理及相关关键科学问题，本项目主要完成了以下研究工作：.1）模糊随机现象建模与分析的基础理论研究。针对实际模糊随机现象建模中常用的一些混合模糊随机变量，定义了LR混合模糊随机变量及严格单调LR混合模糊随机变量，并基于模糊随机事件的平均机会测度提出了新的运算法则。针对模糊随机系统可靠性分析、模糊规划模型求解，基于运算法则提出了新的方法。相比基于模拟的传统方法，这些方法使模糊随机系统分析、模糊规划求解的精度和效率大大提高，为模糊随机环境下的供应链风险建模与分析提供了理论基础。.2）供应链脆弱性及核心企业业务持续能力评估。为了定量分析不确定环境和风险扰动对供应链运营的影响，提出了基于模糊不可操作性投入产出模型的供应链脆弱性评估与分析框架，并以模糊扰动下供应链网络各节点不可操作性水平的波动作为脆弱性评价指标，给出了具体的计算方法。该框架为供应链脆弱性评估与关键脆弱点识别提供了一种有效方法。并提出了基于模糊（概率）贝叶斯网络的供应链核心企业业务持续能力评估方法。.3）供应链脆弱性治理与风险控制。上述供应链脆弱性及企业业务持续能力评估方法也为评价和选择恰当的脆弱性治理措施提供了有效工具。基于这些方法，分析了增加供应商数量、增加供应商或核心企业库存储备等脆弱性缓解措施对供应链风险扰动传播和脆弱性的影响。并进一步从供应链网络规划、供应链业务流程改善、物流战略管理等方面探讨了增强供应链抗风险能力，改善供应链运营绩效的途径和方法。.上述研究还以汽车产业为例，分析了新能源汽车产业链的脆弱性与关键脆弱点，及网络拓补结构和缓解措施对供应链风险扰动传播和脆弱性的影响，探讨了信用交易环境下汽车产业链中的债务风险传播以及核心汽车制造企业的业务持续管理能力，对实际供应链运营管理具有重要应用价值。