Integrated decision-making framework for hospital development: A single-valued neutrosophic probabilistic hesitant fuzzy approach with innovative aggregation operators

Abstract

This research article proposes an innovative algorithm for analyzing parallelism in the evolution of hospital building features, with the goal of advancing decisionmaking processes in both urban and rural hospitals. As an additional generalization of the concepts of fuzzy sets, intuitionistic fuzzy sets, single-valued neutrosophic sets, hesitant fuzzy sets, and probabilistic fuzzy sets this paper proposes a single-valued neutrosophic probabilistic hesitant fuzzy set (SV-NPHFS). It is derived from the combination of single-valued neutrosophic sets, probabilistic fuzzy sets, and hesitant fuzzy sets. The novel algebraic structure and cosine evaluation function of SV-NPHFSs are then introduced. In addition, we introduce novel operators: the single-valued neutrosophic probabilistic hesitant fuzzy weighted geometric (SV-NPHFWG), the single-valued neutrosophic probabilistic hesitant fuzzy ordered weighted geometric (SV-NPHFOWG), the single-valued neutrosophic probabilistic hesitant fuzzy weighted average (SV-NPHFWA), and the single-valued neutrosophic probabilistic hesitant fuzzy ordered weighted average (SV-NPHFOWA). More complex links between features and alternatives can be made with the multi-attribute decision-making procedures outlined in this work. This characteristic highlights their superior practicality and accuracy over existing methods, which often fail to capture the intricate interplay of elements in real-world scenarios. This demonstrates that applying the decision-making strategies covered in this article can lead to the discovery of even additional trait correlations. Finally, we evaluate the performance of our proposed method on a real choice problem and an experimental comparison. The results demonstrate that the new method will be more advantageous in a range of applications where decision-making is uncertain. Figure 1 illustrates all of the manuscript’s results in a graphical abstract.

Keywords

• neutrosophic information
• probabilistic hesitant fuzzy sets
• aggregation operators
• decision making