A novel fuzzy multi-criteria decision-making for enhancing the management of medical waste generated during the coronavirus pandemic

• Published in: Engineering applications of artificial intelligence 2024-07, Vol.133, p.108465, Article 108465
• Main Authors: Demir, Ahmet Turan, Moslem, Sarbast
• Format: Article
• Language: English
• Subjects: Dombi bonferroni mean operator; Fuzzy sets; Medical waste disposal; Multi-criteria decision-making; Preference selection index
• ISSN: 0952-1976; 1873-6769
• DOI: 10.1016/j.engappai.2024.108465

The coronavirus pandemic significantly increased the use of essential medical supplies, resulting in a surge in medical waste generation. This surge has spurred extensive research into sustainable disposal methods for safe and environmentally responsible medical equipment management. Addressing this multifaceted issue falls within the domain of multi-criteria decision-making. This study presents a comprehensive framework for selecting optimal medical waste treatment methods, considering economic, technological, environmental, and social factors. This is the first study to address the problem of selecting a medical waste disposal technology using the Fuzzy Dombi Bonferroni. The mean operator to combine expert opinions, the fuzzy preference selection index method to evaluate the criteria and the fuzzy compromise ranking of alternatives from distance to ideal solution method to rank the alternatives. According to the weightings, the social dimension holds the highest significance at 0.3217. Disinfection efficiency ranks as the most critical criterion, weighing in at 0.0823. The autoclave is rated as the top disposal technique, with a utility function value of 5.4579. Sensitivity analyses ensured the stability and reliability of the models. The adaptability of the applied model to sustainable practices such as energy conversion, material recycling, and resource recovery represents an essential aspect of policymaking in waste management. This assessment can guide policy formulation or improvement processes for waste disposal.