A decision-making framework for green substations: Insights from AHP and fuzzy TOPSIS

In today's dynamic and uncertain environments, effective decision-making processes are essential for navigating complex challenges. This paper proposes an innovative approach utilizing Fermatean fuzzy sets to enhance decision-making within heterogeneous group dynamics. Through a systematic mathematical framework, our method integrates expert preferences to find out the comparative weight of decision attribute, leveraging both Fermatean fuzzy sets and entropy calculations. Furthermore, we introduce a novel technique to assess the significance of individual experts' opinions, accounting for specific contextual factors. By synthesizing performance ratings, criteria weights, and expert inputs, our approach offers a comprehensive decision-making model. We introduce the concept of the proximity coefficient to address existing methodological limitations, enhancing the accuracy of decision outcomes. To validate our methodology, we apply it to a practical scenario involving warehouse location selection. Additionally, analysis of sensitivity is conducted to evaluate the robustness of our method across diverse scenarios, demonstrating its efficacy in uncertain environments. This research contributes to advancing decision-making practices in complex and uncertain contexts, offering a valuable tool for addressing real-world challenges.