A Multi-attribute Decision-Making Context for Hospital Site Evaluation Using Distance Measures Under Complex Picture Fuzzy Soft Set Environment

Abstract

In scenarios containing complex or high-dimensional data, in which conventional distance measures might not be able to accurately portray the subtleties of information interactions, a complex picture fuzzy soft distance measure is crucial. The potential of complex picture fuzzy soft distance measures to manage intricacy, imperfection, and uncertainty across a range of domains is what makes them significant. This article proposes a distance formula based on complex picture fuzzy soft sets (CPiFSs) along with related results in its first phase. Following that, the second phase presents the η-equalities for the proposed distances of CPiFSs. Establishing a hospital is complicated, especially when it comes to choosing the ideal site because it affects mobility and the efficacy of community service. Even though there are several algorithms in the literature those deals with these location-related decision-making challenges, every algorithm has intrinsic flaws that affect how decisions are made. To overcome these challenges, an algorithm based on CPiFS distance measures is presented in the third phase for the evaluation of hospital sites. Finally, the paper concludes by emphasizing the significance of this research and its potential applications in various contexts.