An extended MARCOS approach and generalized Dombi aggregation operators-based group decision-making for emergency logistics suppliers selection utilizing q-rung picture fuzzy information

The evaluation and selection of emergency logistics suppliers (ELSs) is of great significance for improving the disaster relief material reserve system and enhancing the efficient operation of the emergency material guarantee system. Considering the inherent suddenness and uncertainty characteristics of emergency events, this paper establishes a hybrid multi-criteria group decision-making (MCGDM) decision framework under q-rung picture fuzzy (q-RPF) environment to scientifically and reasonably determine the optimal ELS. To begin with, some novel q-RPF operational laws are built based on the generalized Dombi operations, and a series of novel q-RPF aggregation operators are propounded to integrate q-RPF information, as well as some special instances and valuable properties are probed at length. Then a correlation coefficient-based algorithm and q-RPF logarithmic percentage change-driven objective weighting (LOPCOW) method are put forward to identify the weight of expert and assessment criteria, severally. Further, the q-RPF measurement of alternatives and ranking according to compromise solution (MARCOS) method is presented on the basis of the developed operators to ascertain the prioritization of ELSs. Lastly, an empirical that selects the optimal ELS is implemented to validate the practicability and availability of the created q-RPF-LOPCOW–MARCOS framework. The robustness and superiority of the decision framework for ELS selection are verified through sensitivity and comparative analysis. This research proposes a new methodology for evaluating ELSs and can assist emergency managers in quickly and accurately selecting suitable suppliers after emergencies.