An Integrated T-Spherical Fuzzy 2-Tuple Linguistic WASPAS Framework With Hamy Mean Aggregation for Wildlife Conservation Planning

Due to the inherent uncertainty in selecting a best alternative, T-spherical fuzzy 2-tuple linguistic (T-SF2TL) sets will be an advantageous method for decision makers (DMs) to assist their evaluations within T-SF2TL framework. The objective of this study is to establish weighted Hamy mean (WHM) and weighted dual Hamy mean (WDHM) operators within the context of T-SF2TL sets. Meanwhile, the intrinsic attributes of the introduced aggregation operators (AOs) are rigorously assessed to validate their reliability and integrity. Subsequently, we develop a maximization deviation model to evaluate the weights of the criteria in the decision-making process. Furthermore, we extensively discuss essential features and remarks regarding these proposed AOs. Building on the developed AOs, we expand on the weighted aggregated sum product assessment (WASPAS) method to effectively address T-SF2TL decision-making issues. To show the effectiveness and efficacy of the developed approach, we present a real-life problem of wildlife conservation in China and conduct a detailed investigation, comparing it with existing methodologies.