The handling of healthcare waste analysis with an interval-valued Fermatean fuzzy-based decision-making technique

Medical waste risks people and the environment because it can be infectious and contain hazardous substances. For patients to receive medical attention and recover in a safe environment, garbage must be disposed of correctly. Improper medical waste disposal poses a severe risk to society, which can accelerate the development of various pandemics and epidemics. In this case, medical waste disposal should be handled appropriately. This study presents an integrated multi-criteria decision-making method based on an interval-valued Fermatean fuzzy set. In interval-valued Fermatean fuzzy set, the set of all closed intervals in the unit interval [ 0 , 1 ] is used, and membership and non-membership interval values are taken, making it possible to cover many more elements. The study used entropy, Step-wise Weight Assessment Ratio Analysis (SWARA), and Weighted Aggregated Sum Product Assessment (WASPAS) methods defined with interval-valued Fermatean fuzzy numbers. To calculate the criteria weights, the combined entropy-SWARA method is used to compute the objective and subjective weights, respectively. Furthermore, the WASPAS model is utilized to rank alternatives to healthcare waste disposal techniques. After determining the weights of the experts, the rankings of the criteria and alternatives were determined. This method can guarantee high safety and security for health practitioners and society through effective modeling and ranking of risks associated with medical waste disposal. Five alternatives and eight criteria were determined. The analysis for healthcare waste found that incineration ranked highest among other criteria, followed by electromagnetic wave sterilization, disinfection with chemicals, landfill, and encapsulation. In addition, the work’s findings demonstrated that the integrated approach was efficient and helpful in selecting the best disposal technique in healthcare institutions and healthcare waste service companies for healthcare waste management. The performance was then assessed and validated using a sensitivity analysis. For Sensitivity Analysis, experts can adjust the model’s sensitivity by changing the ϑ values. In addition, the study’s findings and their consequences for lawmakers, businesspeople, technologists, and practitioners are examined. In the future, these stakeholders can concentrate on these deficiencies and provide long-term remedies.