Multi-criteria decision-making based on Einstein operators, WASPAS method and quadripartitioned single-valued neutrosophic sets

Plastic waste treatment has become a significant challenge due to the increasing quantities of plastic wastes and increased levels of urbanization. Selecting a suitable plastic waste treatment technology comprises numerous aspects of sustainability. Therefore, it can be considered as a multi-criteria decision-making (MCDM) problem. Uncertainty is widely occurred in such types of realistic problems. The theory of quadripartitioned single-valued neutrosophic set (QSVNS) has emerged as a valuable and flexible tool to manage fuzziness and uncertainties in the data. This work aims to introduce a hybrid MCDM framework based on the standard deviation-based model, the weighted aggregated sum product assessment (WASPAS) approach, Einstein weighted aggregation operators and QSVNSs. In this regard, novel Einstein weighted averaging and geometric operators are introduced to aggregate the quadripartitioned single-valued neutrosophic information. To compute the criteria weights, an integrated quadripartitioned single-valued neutrosophic information-based weighting model is presented through standard deviation. Based on the combination of the proposed Einstein operators and standard deviation-based weighting model, an integrated WASPAS approach is proposed under the context of QSVNSs and further applied to solve the multi-criteria plastic waste treatment technology selection problem, which demonstrates its applicability. Further, sensitivity analysis and comparison with existing approaches are conducted to prove the superiority and rationality of the attained outcomes.