Emergency Decision-Making of Cluster Supply Chain Based on Scenario Analysis and Case-Based Reasoning

Aiming at the unpredictability of cluster supply chain unconventional emergency, this paper proposes a case-based reasoning (CBR) emergency decision-making method for cluster supply chain unconventional emergency based on scenario analysis. In the unconventional emergency scenario, the unconventional emergency scenario knowledge representation structure is constructed based on the pressure-state-response (PSR) model, and then a Bayesian network-based cluster supply chain unconventional emergency scenario analysis network model is created to deduce the characteristic values of emergency decision-making indicators of new cases. The case retrieval algorithm based on the multidimensional cloud model is used for case matching. The weights of indexes are determined based on the entropy weight method. The simulation experiment results verify the effectiveness of the proposed method, which provides theoretical support for the emergency decision-making of unconventional emergency in the cluster supply chain.