Cyclone disaster assessment based on Fermatean hesitant fuzzy information and extended TOPSIS method.

This article focuses on developing and applying aggregation operators based on Fermatean hesitant fuzzy sets (FHFSs) to address uncertainties in multiple attribute decision-making (MADM), specifically for cyclone disaster assessment in Pakistan's Khyber Pakhtunkhwa (KP) province. It introduces novel Fermatean hesitant fuzzy weighted averaging (FHFWA), ordered weighted averaging (FHFOWA), weighted geometric (FHFWG), and ordered weighted geometric (FHFOWG) operators, along with corresponding score and accuracy functions, to effectively aggregate and rank alternatives under uncertainty. The study applies these operators to evaluate cyclone damage across five cities in KP using expert assessments expressed as Fermatean hesitant fuzzy numbers, demonstrating that Mardan is the most severely affected city. Additionally, the article extends the TOPSIS method to the FHFS environment and compares its results with the proposed operators, confirming their reliability and applicability in decision-making problems involving uncertain and hesitant information.