New similarity and divergence measures-based Pythagorean fuzzy MULTIMOORA approach for decision-making problems

Pythagorean fuzzy set (PFS), an extended version of intuitionistic fuzzy set (IFS), is verified to be fastest emerging research discipline and is a significant mode to tackle the imprecise and vague information. It provides a broader representation domain than the IFS. Similarity and divergence measures play paramount role in the field of IFSs’ doctrine as well as PFSs’ doctrine. These measures are integral aspects of utilizing generalized fuzzy sets in real-life problems. In this manuscript, novel similarity and divergence measures for PFSs are developed and compared with extant measures to illustrate their efficiency and reliability. Further, an extended version of multi-objective optimization based on the ratio analysis (MOORA) with the full multiplicative form (MULTIMOORA) approach is introduced by employing developed similarity and divergence measures on PFSs information. To reveal the feasibility and usefulness of the presented approach, a problem of medical equipment supplier selection is discussed from Pythagorean fuzzy perspective. Finally, a comparison with previously developed models is studied to certify the applicability and stability of the introduced MULTIMOORA technique. The outcomes of the work indicate that the present approach is more applicable and efficient than existing techniques under PFSs’ context.