An interval number group decision-making method based on the prospect SMAA-2 model and extended cross-entropy

The preference information of decision-makers (DMs) often cannot be explicitly expressed in complex decision-making environments. Therefore, to address decision-making problems with uncertain preference information, this paper proposes a method based on the prospect SMAA-2 model and extended cross-entropy in interval number environments. We first construct the prospect SMAA-2 model to simulate preference information. This model incorporates central risk-averse and risk-seeking factors, significantly enhancing the ability to identify alternatives. When DMs’ preference information is unknown or partially known, these factors can determine the appropriate level of risk-averse or risk-seeking for alternatives. Next, we devise an extended cross-entropy algorithm based on the continuous ordered weighted harmonic (C-OWH) averaging operator to handle interval numbers. Subsequently, a comprehensive algorithm is designed to derive the weights of DMs, taking into account the relationships among individuals as well as between individuals and the group. Furthermore, we construct the framework for the proposed method. Finally, the applicability of the developed method can be validated by an illustrative example. Comparative analysis is used to verify the rationality and superiority of this method.