Multi-criteria group decision-making method based on einstein power operators, distance measure, additive ratio assessment, and interval-valued q-rung orthopair fuzzy sets

As an extension of q-rung orthopair fuzzy set, interval-valued q-rung orthopair fuzzy set (IVq-ROFS) provides a more wider decision interval to express the fuzziness information. This study aims to propose an integrated multi-criteria group decision-making method based on combination of Einstein power weighted aggregation operators, the distance measure, the stepwise weight assessment ratio analysis (SWARA), and the additive ratio assessment (ARAS) approaches under the context of IVq-ROFSs. In this regard, integrated interval-valued q-rung orthopair fuzzy Einstein power weighted averaging and geometric operators are presented for aggregating the individuals’ information. These operators take the advantages of Einstein and power operations simultaneously and consider the interrelationships between the elements. To compute the decision experts’ weights, a score function-based formula is presented in the context of IVq-ROFSs. To determine the criteria weights, a weight-determination formula is presented with the integration of distance measure-based formula for objective weight and the SWARA for subjective weight of criteria under the context of IVq-ROFS. For this purpose, a new distance measure is proposed to compute the discrepancy between IVq-ROFSs. Few examples are discussed to illustrate the efficiency of the proposed distance measure, which overcomes the limitations of existing interval-valued q-rung orthopair fuzzy distance measures. Based on all of them, a hybrid ARAS method is presented under the context of IVq-ROFSs and used to solve the blockchain network selection problem in the healthcare management system, which illustrates its applicability. To confirm the stability of the obtained outcomes, sensitivity analysis is presented with respect to various values of decision strategy parameter. Comparison with existing approaches is discussed to prove the merits of the proposed approach.