2025/06/12 by Nguyen Thu Huong, Nguyen Tho Thong, Nguyen Thi Lan Nhi +1
Decision Sciences · #Multi-Criteria Decision Making
paper · doi:10.1142/s0219622025500506
The challenge of developing suitable aggregation operators (AOs) is prevalent within the realm of multicriteria decision-making, as these operators are important components in the decision-making process. In real life, the decision-making problem often needs to consider uncertainty, indeterminacy and inconsistency factors with hesitation in estimation, along with considering the relational parameters between multiple attributes. This requires modern approaches in multi-criteria decision-making to better tackle the aforementioned factors. The Generalized Neutrosophic Hypersoft set is a useful extension of the Neutrosophic set theory used to deal with uncertain, indeterminate, and inconsistent information, as well as representing relationships among multiple attributes by hesitant fuzzy numbers in decision processing. Therefore, in this paper, we present the advantages of the Generalized Neutrosophic Hypersoft Einstein aggregation operator and the Generalized Neutrosophic Hypersoft Einstein geometric operator for Generalized Neutrosophic Hypersoft sets, which proficiently handle hesitant neutrosophic data and sub-attributes’ relationships. Subsequently, we propose a new MCDM model that utilizes the proposed operators in a Generalized Neutrosophic Hypersoft environment. Ultimately, to illustrate the utility and efficacy of our model, a real-world case study investigates the selection of strategies for tobacco control. The findings confirm the feasibility of the proposed methodology to address MCDM within the context of the Generalized Neutrosophic Hypersoft environment, such as developing an MCDM model for prioritizing an effective policy in reducing cigarette use.