Fermatean Fuzzy IWP-TOPSIS-GRA Multi-Criteria Group Analysis and Its Application to Healthcare Waste Treatment Technology Evaluation

Abstract

The growth of healthcare waste (HCW) was driven by the spread of COVID-19. Effective HCW eradication has become a pressing global issue that requires immediate attention. Selecting an effective healthcare waste treatment technology (HCWTT) can aid in preventing waste buildup. HCWTT selection can be seen as a complex multi-criteria group evaluation problem as the process involves multiple types of criteria and decision-makers (DMs) facing uncertain and vague information. The key objective of this study is to create a useful tool for the evaluation of HCWTT that is appropriate for the organization’s needs. A novel index system for assessing the HCWTT during the decision-making evaluation process is first presented. Then a new approach based on entropy measure, decision-making trial and evaluation laboratory (DEMATEL), and game theory for the integrated weighting procedure (IWP) is presented under a Fermatean fuzzy environment. A multi-criteria group analysis based on IWP, a technique for order of preference by similarity to ideal solution (TOPSIS) and grey relational analysis (GRA), named IWP-TOPSIS-GRA framework suited to Fermatean fuzzy evaluation information, is developed. In a real-world case of HCWTT selection, through comparative analysis and sensitivity analysis, it is verified that the presented method is feasible and robust.