Research uncovers efficient waste management strategies using complex spherical fuzzy sets, highlighting decision-making complexities.
Industrial waste involves any hazardous substance, chemical, or byproduct and waste discharged during the operation of an industry. Due to its nature and probable detriment to the environment, industrial waste is a great matter of concern for governments all over the world. Selection of industry‐linked industrial waste management strategies (IWMSs) is the main objective of this research endeavor. Applying greater generality in the dimensions of the abovementioned applications could potentially enhance a lot of their efficiency. Einstein norms/application of Einstein operations have not been effectively applied within the complex spherical fuzzy sets (CSFSs) framework as such; this study now advances the application of Einstein operators in CSFS which would provide an adiaphorous approach to solving issues related to decision‐making problems (DMPs). The actual situations in which decisions are made invariably present numerous conflicting factors, which complicate the process even further. The methodology of multiattribute group decision‐making (MAGDM) is an essential means of handling such situations. This paper deals with the challenge pertaining to MAGDM and utilizes the established Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). In order to aid successful problem‐solving, new aggregation operators are proposed, namely, complex spherical fuzzy Einstein weighted averaging (CSFEWA) operator, complex spherical fuzzy Einstein ordered weighted averaging (CSFEOWA) operator, and complex spherical fuzzy Einstein hybrid weighted averaging (CSFEHWA) operator.
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Rahman et al. (2025) studied this question.
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