Interval-valued Fermatean fuzzy Dombi aggregation operators and SWARA

Choosing the most capable organization to manage biomedical waste (BMW) is a typical multi-attribute group decision-making (MAGDM) problem. MAGDM is frequently used to deal with decision-making scenarios that are fraught with uncertainty and vagueness. As a novel extension of the fuzzy set, the interval-valued Fermatean fuzzy set (IVFFS) can more extensively express the uncertain and vague data in MAGDM issues. In order to combine the information of IVFFS, in this paper, we develop interval-valued Fermatean fuzzy Dombi weighted averaging (geometric) operators with the assistance of Dombi operations. The developed operators can consider the extremely large data sets and the relationships between all decision attributes. Then, utilizing our proposed aggregation operators, we present an integrated MAGDM methodology by combining Preference Ranking Organization METhod for Enrichment Evaluation II (PROMETHEE II) and Stepwise Weight Assessment Ratio Analysis (SWARA) methods. To do this, the attribute weights are estimated by the SWARA method and the PROMETHEE II method determines the preference order of the options. Afterwards, to illustrate the practicality of the proposed methodology, we consider a case study about selecting the most capable organization among the available ones that can handle BMW. The result of this study shows that the bio-chemistry lab is the best BMW management organization. Sensitivity and comparative analysis demonstrate the stability and reliability of the proposed method. According to the findings of this study, we conclude that the proposed methodology offers a comprehensive and systematic approach to evaluating BMW organizations within the IVFF context.