(School of Business,Central South University,Changsha 410083,China)
This paper proposes a dynamic large group emergency decision-making method considering time series, aiming at the time-series related problem with unknown expert weight, attribute weight and stage weight. Firstly, a distance formula considering the hesitation degree of interval intuitionistic fuzzy numbers is proposed, and the approximation degree of interval intuitionistic fuzzy numbers is defined. Comprehensively considering the approximation degree and similarity, the preference information of large groups of experts is clustered using the fuzzy clustering method. Then, aiming at the shortage of the existing interval intuitionistic fuzzy entropy formula, a new interval intuitionistic fuzzy entropy formula is proposed. Based on this formula, considering the difference of knowledge level among experts and the non-heritability of preference information in each stage, the weights of experts under different attributes and that of attributes under different stages are calculated. Considering the influence of time series on the weight of each stage, the relative entropy model is constructed to determine the stage weights reasonably, and then the weighted average operator is used to obtain the comprehensive group preference of each program in the whole decision process. And the comprehensive group preferences of each scheme in the whole decision-making process are obtained by using the weighted average operator. The scheme is ranked by using the score function and the exact function of the interval intuitionistic fuzzy set, and the optimal scheme is selected. Finally, the validity and superiority of the proposed method are verified by comparing it with the methods in previous literatures.