Abstract

Decision-makers (DMs) usually encounter the problem of preference transfer when making decisions about emergencies in a complex environment. We propose a new method for dynamic emergency decision-making for large-group risk based on cumulative prospect theory (CPT). First, the preference judgment matrix is used to aggregate the DMs’ preferences in different event states. Second, because of the complexity of the number of decisions proposed by a large group, a clustering method is used to cluster the preferences of the decision-making group and obtain a number of different aggregations with corresponding weights. Then, given that the risk preferences of the DMs affect the decision result, CPT is used to calculate the overall outlook value for large-group decision-making. Finally, DMs need to adjust the preference judgment matrix according to changes in event states. After several stages of adjustment, the Markov chain for the current development state and the DMs’ preference transfer matrix are obtained. The optimal scheme for the current state is given as a combination of the preference transfer matrix and the overall outlook value for the large group. Using this method, DMs can obtain the best scheme for different states in advance and make an emergency plan to reduce the risk of preference transfer. A case study is used to illustrate the rationality and effectiveness of the proposed method.

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