In this investigation, we have put forward a novel multi-criteria decision-making (MCDM) technique, intuitionistic fuzzy best-worst method (intuitionistic fuzzy BWM). Moreover, we have designed a novel hybrid MCDM technique called intuitionistic fuzzy best-worst analytic hierarchy process (intuitionistic fuzzy BWAHP) which is the amalgamation of intuitionistic fuzzy BWM and analytic hierarchy process (AHP). In this study, BWM finds its use to evaluate the weightage (or priority value) of criteria, and using AHP, the local weights of alternatives are decided. The proposed technique is utilized to recognize the most significant alternative (or indicator), for the efficiency of a water treatment plant. Observing the result, it can be said that the 'water quality' is the most responsible alternative. The consistency ratio value which is found by our proposed method is less, compared to the existing BWM and fuzzy BWM techniques. Finally, using a comparative study and sensitivity analysis, we verify the findings produced by our proposed method.

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In this work, a novel fuzzy decision making technique namely trapezoidal fuzzy Best-Worst method (fuzzy BWM) is developed which is based on Best-Worst method (BWM) and Trapezoidal fuzzy number. The real motive behind our work is to take a broad view of the existing fuzzy BWM based on triangular fuzzy number by trapezoidal fuzzy number. Also, we have presented a new hybrid MCDM technique called as Trapezoidal fuzzy Best Worst Analytic Hierarchy based on proposed trapezoidal fuzzy BWM and existing trapezoidal fuzzy Analytic Hierarchy Process (AHP). BWM approach is employed in evaluating the PV of considering criteria and trapezoidal fuzzy AHP is used to assess the local priority vale (PV) of considering alternatives (or indicators) of a decision problem. Moreover it used to identify the most significant alternative which is responsible for performance efficiency of a hydro power plant under climatic scenario. From the result, it is undoubtedly found that hydraulic had is most responsible indicator. Further, the CR (consistency ratio) value which is determined by our proposed trapezoidal fuzzy BWM is less than that of existing BWM and fuzzy BWM techniques. Finally, we have validated our result by comparative study, scenario analysis and sensitivity analysis.

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