A Novel Intuitionistic Fuzzy Distance Measure-SWARA-COPRAS Method for Multi-Criteria Food Waste Treatment Technology Selection
As an extension of fuzzy set, intuitionistic fuzzy set (IFS) considers the degrees of non-membership and hesitancy along with the degree of membership, therefore, the knowledge and semantic representation of IFS become more significant, resourceful and appropriate. However, with the presence of multiple sustainability indicators and uncertain information, the selection of appropriate food waste treatment technology (FWTT) can be considered as a multi-criteria decision-making (MCDM) problem. Thus, this study aims to introduce a decision support system for assessing the FWTT alternative under uncertain environment. For this purpose, a new intuitionistic fuzzy information-based MCDM methodology is proposed by combining intuitionistic fuzzy distance measure, stepwise weight assessment ratio analysis (SWARA) and the complex proportional assessment (COPRAS) methods. The combination of distance measure-based procedure and SWARA method is used to take the benefits of both the objective and subjective weights of criteria during FWTTs evaluation. Next, the hybridized COPRAS methodology is presented to assess and rank the considered FWTTs from sustainability perspective under intuitionistic fuzzy environment. Further, the present method is implemented on a case study of FWTT selection problem within the context of IFS, which shows its feasibility and effectiveness. This method not only reflects the subjective perspective of decision expert but also captures the objective evaluation of the actual performance measures of each FWTT candidate. Sensitivity and comparative analyses show a high degree of robustness and uniformity in the obtained results. Obtained outcomes point out that the present COPRAS model can effectively choose the suitable FWTT candidate and have the potential to offer practical reference for the policymakers.
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