Researcher from Near East University have made significant contributions to a study focusing on optimization techniques and aggregation operators in the context of interval-valued Pythagorean fuzzy hypersoft sets (IVPFHSS). This novel research extends the application of aggregation operators to IVPFHSS, a comprehensive system providing a more adept handling of imprecise information in decision-making processes.
The study introduces interactive operational laws for IVPFHSS, presenting innovative operators like the interval-valued Pythagorean fuzzy hypersoft interactive weighted average (IVPFHSIWA) and interval-valued Pythagorean fuzzy hypersoft interactive weighted geometric (IVPFHSIWG) operators. These operators are characterized by essential properties such as Idempotency, Boundedness, and Homogeneity. The proposed multi-criteria group decision-making (MCGDM) model addresses existing shortcomings in conventional approaches, offering a more effective and consistent method for dealing with inaccurate data based on IVPFHSS.
In the domain of decision-making, IVPFHSS proves to be a robust mathematical structure for handling indefinite and unreliable data, expanding the possibilities of identifying optimal alternatives. The research emphasizes the importance of paying close attention to objectives and proposes a new approach for selecting sustainable suppliers under the IVPFHSS setting. By overcoming the challenges of interactions and complex scenarios, the study provides a comprehensive methodology for evaluating and selecting green thermal power equipment suppliers, ensuring robust decision-making in flexible and uncertain environments.
The proposed operators and decision-making approach are validated through mathematical examples, demonstrating their superiority in addressing the challenges of MCGDM. The study also sets the stage for future research, suggesting extensions to interval-valued q-rung orthopair fuzzy hypersoft sets and their application in various fields such as medical diagnosis, material selection, pattern recognition, information fusion, and supply chain management.
This research not only contributes to the theoretical development of decision-making methodologies but also presents practical implications for addressing complex challenges in real-world scenarios. The findings underscore the potential impact of these innovative approaches on optimizing decision processes in diverse applications.
More Information:
https://www.aimspress.com/aimspress-data/math/2023/6/PDF/math-08-06-750.pdf
