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"

Tian Zhang, Jianwei Gao, Haoyu Liu, Qinliang Tan, Yaping Wang and Ningbo Huang

Journal of the Operational Research Society, 2025, vol. 76, issue 10, 2020-2038

Abstract: 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.

Date: 2025
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DOI: 10.1080/01605682.2025.2450289

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