Optimizing Healthcare Facility Allocation Using Fuzzy N-Bipolar Soft Expert Decision Approach

Abstract

Efficient planning in the healthcare sector requires selecting the most suitable facility location based on multiple, often conflicting criteria and expert evaluations. This study proposes Fuzzy N-Bipolar Soft Expert (FN-BSE) set model, which integrates expert input, bipolar assessments, and multinary evaluation within a fuzzy framework. Theoretical structure of the model is developed through fundamental operations and their algebraic properties. Applying FN-BSE set model to a case study of seven potential healthcare locations, expert judgments were aggregated, and alternatives were ranked. The results indicate that location ω₃ is the optimal choice. Analysis of positive and negative evaluations shows the model effectively balances conflicting opinions, and comparative evaluation demonstrates its superiority over existing approaches in handling uncertainty and supporting robust Multi-Attribute Group Decision-Making (MAGDM).