A Conflict Style Large Group Dynamic Emergency Decision-Making Method Based on Time Series.

Due to the dynamic, complex and unpredictable characteristics of unconventional emergencies, which greatly enhances the difficulty of emergency decision-making. A new decision-making method is proposed for the large-group dynamic emergency decision-making problem with unknown expert weight and stage weight which is related to time series. Firstly, we propose a distance formula considering the hesitancy degree of the interval-value intuitionistic fuzzy number and define the closeness of the interval-value intuitionistic fuzzy number. The preference information of experts in each stage is clustered by combining the closeness and similarity. Secondly, we propose a new formula to make up the shortcomings of the existing interval-value intuitionistic fuzzy entropy formulas. Considering the difference of knowledge level among experts and the nonhereditary characteristics of preference information in each stage, we use this formula to calculate the weight of experts under each attribute. Thirdly, considering the influence of time series on stage weights, we reasonably determine the aggregation weight and stage weight in order to reduce the conflict. Then we rank the alternatives according to comprehensive large group preference information. Finally, a case study verifies the validity and superiority of the proposed method.