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

Abstract

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.

An extended picture fuzzy multicriteria group decision analysis with different weights: A case study of COVID-19 vaccine allocation

“…Hezam et al [ 23 ] proposed a robus methodology for allocating COVID vaccines, but it shows limitations from the manegerial implications and practical perpectives. Due to space limitations, other works related to vaccination strategies and MCGDM fuzzy methods as [ [24] , [25] , [26] , [27] , [28] ] are not discussed. However from all literature availabe in the field, most of it showed the limitations that were previously mentioned.…”

A Multi-Criteria Decision-Making Model with Interval-Valued Intuitionistic Fuzzy Sets for Evaluating Digital Technology Strategies in COVID-19 Pandemic Under Uncertainty

“…Alkan and Kahreman [ 23 ] introduced the q-rung orthopedic fuzzy TOPSIS method to select an appropriate government strategy during the COVID-19 pandemic. Narayanamoorthy et al [ 24 ] evaluated the vaccination of Youngsters in the COVID-19 pandemic condition by PROMETHEE-II in an IF environment. Tumsekcali et al [ 25 ] proposed an IVIF-based methodology during the COVID-19 pandemic.…”

COVID-19 and Chikungunya: an optimal control model with consideration of social and environmental factors

“…Moreover, two actions were investigated for controlling the epidemic, namely, quarantine, and hospitalization. Also, some articles addressed the optimal distribution of vaccines, such as Narayanamoorthy et al ( 2021 ), Hezam et al ( 2021b ) or discussed the humanitarian response plan for high-priority countries as an optimal distribution model (Hezam 2021a ).…”