The COVID-19 Vaccine Preference for Youngsters Using PROMETHEE-II in the IFSS Environment

• Published in: Symmetry (Basel) Vol. 13; no. 6; p. 1030
• Main Authors: Narayanamoorthy, Samayan, Pragathi, Subramaniam, Parthasarathy, Thirumalai Nallasivan, Kalaiselvan, Samayan, Kureethara, Joseph Varghese, Saraswathy, Ranganathan, Nithya, Poosamani, Kang, Daekook
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01-06-2021
• Subjects: Coronaviruses; COVID-19 vaccine; COVID-19 vaccines; Decision making; extension of PROMETHEE-II; Feasibility; Fuzzy sets; Immunization; intuitionistic fuzzy soft set; Multiple criterion; preference structure; Ranking; Vaccines; Young adults
• ISSN: 2073-8994; 2073-8994
• DOI: 10.3390/sym13061030

Extensive decision-making during the vaccine preparation period is unpredictable. An account of the severity of the disease, the younger people with COVID-19 comorbidities and other chronic diseases are also at a higher risk of the COVID-19 pandemic. In this research article, the preference ranking structure for the COVID-19 vaccine is recommended for young people who have been exposed to the effects of certain chronic diseases. Multiple Criteria Decision-Making (MCDM) approach effectively handles this vague information. Furthermore, with the support of the Intuitionistic Fuzzy Soft Set (IFSS), the entries under the new extension of the Preference Ranking Organization Method for Enrichment Evaluation-II (PROMETHEE-II) is suggested for Preference Ranking Structure. The concept of intuitionistic fuzzy soft sets is parametric in nature. IFSS suggests how to exploit an intuitionistic ambiguous input from a decision-maker to make up for any shortcomings in the information provided by the decider. The weight of the inputs is calculated under the Intuitionistic Fuzzy Weighted Average (IFWA) operator, the Simply Weighted Intuitionistic Fuzzy Average (SWIFA) operator, and the Simply Intuitionistic Fuzzy Average (SIFA) operator. An Extended PROMETHEE-based ranking, outranking approach is used, and the resultant are recommended under the lexicographic order. Its sustainability and feasibility are explored for three distinct priority structures and the possibilities of the approach. To demonstrate the all-encompassing intuitionistic fuzzy PROMETHEE approach, a practical application regarding COVID-19 severity in patients is given, and then it is compared to other existing approaches to further explain its feasibility, and the sensitivity of the preference structure is examined according to the criteria.