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Abstract

Uncertain sporadic risks have prominent features such as small probability, difficult to predict, fast diffusion, and complex types, which greatly increase the difficulty of control. Severe incidental risk events often affect the normal operation of the supply chain system, so it is particularly important to respond to risks in a timely and effective manner. Based on fuzzy logic, this paper studies the coping strategies of three-level supply chain systems composed of manufacturers, distribution centers and retailers under uncertain risks. Firstly, fuzzy logic is used to highly quantify fuzzy variables to calculate specific changes caused by the uncertain risks to members in supply chain, and effectively predict overall changes of the supply chain system; Secondly, the member information is updated in the post-change supply chain system. On this basis, the member maximum loss model is established, the maximum loss amount and the amount of each strategy loss are calculated, and a risk response strategy plan is formulated. Finally, a coping strategy is stored for a quick call when similar risks occur again. The feasibility and effectiveness of the model and method are verified by specific examples and variable sensitivity analysis.

Keywords

Manufacturing supply chain risk response maximum loss decision analysis fuzzy logic

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Research on supply chain risk coping strategy based on fuzzy logic

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