An outranking method with Dombi aggregation operators based on multi-polar fuzzy Z-numbers for selection of best rehabilitation center

Abstract

Useful decisions are made based on reliable information. The concept of $Z$-number involves the issue of reliability of information. Multipolar information is particularly important in scenarios involving multiple attributes in a decision making process. There does not exist a study in the literature that conveys multipolar information with reliability. In this research article, the concept of multipolar fuzzy $Z$-Dombi aggregation operators is first introduced. An outranking method based on the proposed multipolar fuzzy $Z$-Dombi aggregation operators is then developed. The proposed method is applied to a case study related to the selection of the best rehabilitation centre for the treatment of teenage drug users. The proposed method is compared with four existing techniques in multipolar fuzzy and fuzzy environments to validate the approach. A sensitivity analysis is performed to test the credibility of the study. Further, the Spearman coefficient is calculated for ranking lists obtained by different methods to verify the method’s consistency. The study’s findings are presented in graphical illustrations for a clear understanding of the results. The method shows validity through consistent comparison with four established techniques. This alignment supports its robustness and relevance in practical applications. Moreover, a positive Spearman correlation coefficient confirms its reliability by aligning rankings with expected outcomes.