An applied study of multi-stage multi-attribute group decision-making based on intuitionistic fuzzy sets—selection of hydrogen energy projects in the context of “dual-carbon"

In group decision-making scenarios involving intuitionistic fuzzy numbers for attribute values, attribute weights tend to be subjective. To enhance objectivity and scientific rigor in decision-making, this study develops a multi-stage, multi-attribute group decision-making model based on intuitionistic fuzzy sets. The model integrates both subjective and objective attribute weights and uses a product method to calculate comprehensive weights. A new “double-consideration” method is proposed to determine time weights, making it particularly suitable for multi-stage decision-making. The model also aggregates multi-stage information through an intuitionistic fuzzy weighted average operator and employs Pearson’s correlation coefficient to assign expert weights, promoting group consensus. The improved TOPSIS (G-TOPSIS) method is then applied to the selection of hydrogen energy projects within the “dual-carbon” framework. Comparative and sensitivity analyses verify the model’s feasibility and effectiveness, offering valuable guidance for hydrogen energy project selection in alignment with “dual-carbon” goals.